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28th KDD 2022: Washington, DC, USA
- Aidong Zhang, Huzefa Rangwala:
KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022. ACM 2022, ISBN 978-1-4503-9385-0
Keynote Talks
- Lise Getoor:
The Power of (Statistical) Relational Thinking. 1 - Milind Tambe:
AI for Social Impact: Results from Deployments for Public Health and Conversation. 2 - Shang-Hua Teng:
Beyond Traditional Characterizations in the Age of Data: Big Models, Scalable Algorithms, and Meaningful Solutions. 3
Research Track Full Papers
- Sarp Aykent, Tian Xia:
GBPNet: Universal Geometric Representation Learning on Protein Structures. 4-14 - Guangji Bai, Liang Zhao:
Saliency-Regularized Deep Multi-Task Learning. 15-25 - Wei-Xuan Bao, Jun-Yi Hang, Min-Ling Zhang:
Submodular Feature Selection for Partial Label Learning. 26-34 - Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler:
Motif Prediction with Graph Neural Networks. 35-45 - Di Chai, Leye Wang, Junxue Zhang, Liu Yang, Shuowei Cai, Kai Chen, Qiang Yang:
Practical Lossless Federated Singular Vector Decomposition over Billion-Scale Data. 46-55 - Deepayan Chakrabarti:
Avoiding Biases due to Similarity Assumptions in Node Embeddings. 56-65 - Mohna Chakraborty, Adithya Kulkarni, Qi Li:
Open-Domain Aspect-Opinion Co-Mining with Double-Layer Span Extraction. 66-75 - Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran:
Multi-Variate Time Series Forecasting on Variable Subsets. 76-86 - Jiayi Chen, Aidong Zhang:
FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks. 87-96 - Jin Chen, Guanyu Ye, Yan Zhao, Shuncheng Liu, Liwei Deng, Xu Chen, Rui Zhou, Kai Zheng:
Efficient Join Order Selection Learning with Graph-based Representation. 97-107 - Jingfan Chen, Wenqi Fan, Guanghui Zhu, Xiangyu Zhao, Chunfeng Yuan, Qing Li, Yihua Huang:
Knowledge-enhanced Black-box Attacks for Recommendations. 108-117 - Liyi Chen, Zhi Li, Tong Xu, Han Wu, Zhefeng Wang, Nicholas Jing Yuan, Enhong Chen:
Multi-modal Siamese Network for Entity Alignment. 118-126 - Man-Sheng Chen, Chang-Dong Wang, Dong Huang, Jian-Huang Lai, Philip S. Yu:
Efficient Orthogonal Multi-view Subspace Clustering. 127-135 - Mouxiang Chen, Chenghao Liu, Zemin Liu, Jianling Sun:
Scalar is Not Enough: Vectorization-based Unbiased Learning to Rank. 136-145 - Weiqi Chen, Wenwei Wang, Bingqing Peng, Qingsong Wen, Tian Zhou, Liang Sun:
Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting. 146-156 - Xingguang Chen, Fangyuan Zhang, Sibo Wang:
Efficient Approximate Algorithms for Empirical Variance with Hashed Block Sampling. 157-167 - Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. 168-178 - Kewei Cheng, Jiahao Liu, Wei Wang, Yizhou Sun:
RLogic: Recursive Logical Rule Learning from Knowledge Graphs. 179-189 - Zhi Cheng, Xiu Su, Xueyu Wang, Shan You, Chang Xu:
Sufficient Vision Transformer. 190-200 - Eli Chien, Puoya Tabaghi, Olgica Milenkovic:
HyperAid: Denoising in Hyperbolic Spaces for Tree-fitting and Hierarchical Clustering. 201-211 - Ranak Roy Chowdhury, Xiyuan Zhang, Jingbo Shang, Rajesh K. Gupta, Dezhi Hong:
TARNet: Task-Aware Reconstruction for Time-Series Transformer. 212-220 - Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii:
Scalable Differentially Private Clustering via Hierarchically Separated Trees. 221-230 - Qianhao Cong, Jing Tang, Kai Han, Yuming Huang, Lei Chen, Yeow Meng Chee:
Noisy Interactive Graph Search. 231-240 - Sen Cui, Jian Liang, Weishen Pan, Kun Chen, Changshui Zhang, Fei Wang:
Collaboration Equilibrium in Federated Learning. 241-251 - Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun:
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. 252-262 - Sebastian Dalleiger, Jilles Vreeken:
Discovering Significant Patterns under Sequential False Discovery Control. 263-272 - Khalil Damak, Sami Khenissi, Olfa Nasraoui:
Debiasing the Cloze Task in Sequential Recommendation with Bidirectional Transformers. 273-282 - Debanjan Datta, Feng Chen, Naren Ramakrishnan:
Framing Algorithmic Recourse for Anomaly Detection. 283-293 - Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Robust Event Forecasting with Spatiotemporal Confounder Learning. 294-304 - Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, Yongdong Zhang:
Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. 305-315 - Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li:
On Structural Explanation of Bias in Graph Neural Networks. 316-326 - Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach:
Fair Labeled Clustering. 327-335 - Chenguang Fang, Shaoxu Song, Yinan Mei, Ye Yuan, Jianmin Wang:
On Aligning Tuples for Regression. 336-346 - Ziquan Fang, Yuntao Du, Xinjun Zhu, Danlei Hu, Lu Chen, Yunjun Gao, Christian S. Jensen:
Spatio-Temporal Trajectory Similarity Learning in Road Networks. 347-356 - Kaituo Feng, Changsheng Li, Ye Yuan, Guoren Wang:
FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks. 357-366 - Dongqi Fu, Liri Fang, Ross Maciejewski, Vetle I. Torvik, Jingrui He:
Meta-Learned Metrics over Multi-Evolution Temporal Graphs. 367-377 - Tianfan Fu, Jimeng Sun:
SIPF: Sampling Method for Inverse Protein Folding. 378-388 - Tianfan Fu, Jimeng Sun:
Antibody Complementarity Determining Regions (CDRs) design using Constrained Energy Model. 389-399 - Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán:
Optimal Interpretable Clustering Using Oblique Decision Trees. 400-410 - Dawei Gao, Yuexiang Xie, Zimu Zhou, Zhen Wang, Yaliang Li, Bolin Ding:
Finding Meta Winning Ticket to Train Your MAML. 411-420 - Yunjun Gao, Xiaoze Liu, Junyang Wu, Tianyi Li, Pengfei Wang, Lu Chen:
ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities. 421-431 - Yuyang Gao, Tong Steven Sun, Guangji Bai, Siyi Gu, Sungsoo Ray Hong, Liang Zhao:
RES: A Robust Framework for Guiding Visual Explanation. 432-442 - Yuxia Geng, Jiaoyan Chen, Wen Zhang, Yajing Xu, Zhuo Chen, Jeff Z. Pan, Yufeng Huang, Feiyu Xiong, Huajun Chen:
Disentangled Ontology Embedding for Zero-shot Learning. 443-453 - Ehsan Gholami, Mohammad Motamedi, Ashwin Aravindakshan:
PARSRec: Explainable Personalized Attention-fused Recurrent Sequential Recommendation Using Session Partial Actions. 454-464 - Rahul Ghosh, Arvind Renganathan, Kshitij Tayal, Xiang Li, Ankush Khandelwal, Xiaowei Jia, Christopher J. Duffy, John Nieber, Vipin Kumar:
Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology. 465-474 - Xingzhi Guo, Baojian Zhou, Steven Skiena:
Subset Node Anomaly Tracking over Large Dynamic Graphs. 475-485 - Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J. Smola:
BLISS: A Billion scale Index using Iterative Re-partitioning. 486-495 - Vinayak Gupta, Srikanta Bedathur:
ProActive: Self-Attentive Temporal Point Process Flows for Activity Sequences. 496-504 - Seok-Ju Hahn, Minwoo Jeong, Junghye Lee:
Connecting Low-Loss Subspace for Personalized Federated Learning. 505-515 - Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong:
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction. 516-524 - Xin Han, Ye Zhu, Kai Ming Ting, De-Chuan Zhan, Gang Li:
Streaming Hierarchical Clustering Based on Point-Set Kernel. 525-533 - Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu:
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. 534-544 - Shuo He, Lei Feng, Fengmao Lv, Wen Li, Guowu Yang:
Partial Label Learning with Semantic Label Representations. 545-553 - Wenchong He, Zhe Jiang, Marcus Kriby, Yiqun Xie, Xiaowei Jia, Da Yan, Yang Zhou:
Quantifying and Reducing Registration Uncertainty of Spatial Vector Labels on Earth Imagery. 554-564 - Catherine F. Higham, Desmond J. Higham, Francesco Tudisco:
Core-periphery Partitioning and Quantum Annealing. 565-573 - Dat Hong, Alberto Maria Segre, Tong Wang:
AdaAX: Explaining Recurrent Neural Networks by Learning Automata with Adaptive States. 574-584 - Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Towards Universal Sequence Representation Learning for Recommender Systems. 585-593 - Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, Jie Tang:
GraphMAE: Self-Supervised Masked Graph Autoencoders. 594-604 - Jiaxin Huang, Yu Meng, Jiawei Han:
Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation. 605-614 - Zijian Huang, Meng-Fen Chiang, Wang-Chien Lee:
LinE: Logical Query Reasoning over Hierarchical Knowledge Graphs. 615-625 - Alexis Huet, José Manuel Navarro, Dario Rossi:
Local Evaluation of Time Series Anomaly Detection Algorithms. 635-645 - Bo Hui, Wei-Shinn Ku:
Low-rank Nonnegative Tensor Decomposition in Hyperbolic Space. 646-654 - Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian:
Global Self-Attention as a Replacement for Graph Convolution. 655-665 - Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder:
Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles. 666-675 - Roshni G. Iyer, Yunsheng Bai, Wei Wang, Yizhou Sun:
Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs. 676-686 - Yingsheng Ji, Zheng Zhang, Xinlei Tang, Jiachen Shen, Xi Zhang, Guangwen Yang:
Detecting Cash-out Users via Dense Subgraphs. 687-697 - Shengmin Jin, Hao Tian, Jiayu Li, Reza Zafarani:
A Spectral Representation of Networks: The Path of Subgraphs. 698-708 - Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. 709-719 - Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin:
Condensing Graphs via One-Step Gradient Matching. 720-730 - Yilun Jin, Kai Chen, Qiang Yang:
Selective Cross-City Transfer Learning for Traffic Prediction via Source City Region Re-Weighting. 731-741 - Jian Kang, Qinghai Zhou, Hanghang Tong:
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks. 742-752 - Matti Karppa, Rasmus Pagh:
HyperLogLogLog: Cardinality Estimation With One Log More. 753-761 - Jayoung Kim, Chaejeong Lee, Yehjin Shin, Sewon Park, Minjung Kim, Noseong Park, Jihoon Cho:
SOS: Score-based Oversampling for Tabular Data. 762-772 - Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zhang, Miltiadis Allamanis:
CoRGi: Content-Rich Graph Neural Networks with Attention. 773-783 - Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Woosuk Kwon, Joseph Hassoun, Kurt Keutzer:
Learned Token Pruning for Transformers. 784-794 - Seonggyeom Kim, Dong-Kyu Chae:
ExMeshCNN: An Explainable Convolutional Neural Network Architecture for 3D Shape Analysis. 795-803 - Yeachan Kim, Bonggun Shin:
In Defense of Core-set: A Density-aware Core-set Selection for Active Learning. 804-812 - Furkan Kocayusufoglu, Arlei Silva, Ambuj K. Singh:
FlowGEN: A Generative Model for Flow Graphs. 813-823 - Danning Lao, Xinyu Yang, Qitian Wu, Junchi Yan:
Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation. 824-834 - Xiaoliang Lei, Hao Mei, Bin Shi, Hua Wei:
Modeling Network-level Traffic Flow Transitions on Sparse Data. 835-845 - Collin Leiber, Lena G. M. Bauer, Michael Neumayr, Claudia Plant, Christian Böhm:
The DipEncoder: Enforcing Multimodality in Autoencoders. 846-856 - Han Li, Dan Zhao, Jianyang Zeng:
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction. 857-867 - Haoran Li, Hanghang Tong, Yang Weng:
Domain Adaptation in Physical Systems via Graph Kernel. 868-876 - Jiajun Li, Zhewei Wei, Bolin Ding, Xiening Dai, Lu Lu, Jingren Zhou:
Sampling-based Estimation of the Number of Distinct Values in Distributed Environment. 893-903 - Jiatong Li, Fei Wang, Qi Liu, Mengxiao Zhu, Wei Huang, Zhenya Huang, Enhong Chen, Yu Su, Shijin Wang:
HierCDF: A Bayesian Network-based Hierarchical Cognitive Diagnosis Framework. 904-913 - Junyi Li, Jian Pei, Heng Huang:
Communication-Efficient Robust Federated Learning with Noisy Labels. 914-924 - Kuan Li, Yang Liu, Xiang Ao, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He:
Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN. 925-935 - Rongfan Li, Ting Zhong, Xinke Jiang, Goce Trajcevski, Jin Wu, Fan Zhou:
Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning. 936-944 - Shuo Li, Xiayan Ji, Edgar Dobriban, Oleg Sokolsky, Insup Lee:
PAC-Wrap: Semi-Supervised PAC Anomaly Detection. 945-955 - Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, Bin Cui:
TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning. 956-966 - Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, Bin Cui:
Transfer Learning based Search Space Design for Hyperparameter Tuning. 967-977 - Yinghao Li, Le Song, Chao Zhang:
Sparse Conditional Hidden Markov Model for Weakly Supervised Named Entity Recognition. 978-988 - Lu Lin, Ethan Blaser, Hongning Wang:
Graph Structural Attack by Perturbing Spectral Distance. 989-998 - Sikun Lin, Shuyun Tang, Scott T. Grafton, Ambuj K. Singh:
Deep Representations for Time-varying Brain Datasets. 999-1009 - Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao:
Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems. 1010-1020 - Aiwei Liu, Xuming Hu, Li Lin, Lijie Wen:
Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graph. 1021-1030 - Chengchang Liu, Shuxian Bi, Luo Luo, John C. S. Lui:
Partial-Quasi-Newton Methods: Efficient Algorithms for Minimax Optimization Problems with Unbalanced Dimensionality. 1031-1041 - Dachuan Liu, Jin Wang, Shuo Shang, Peng Han:
MSDR: Multi-Step Dependency Relation Networks for Spatial Temporal Forecasting. 1042-1050 - Dugang Liu, Mingkai He, Jinwei Luo, Jiangxu Lin, Meng Wang, Xiaolian Zhang, Weike Pan, Zhong Ming:
User-Event Graph Embedding Learning for Context-Aware Recommendation. 1051-1059 - Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Adelaide Woicik, Sheng Wang:
Graph-in-Graph Network for Automatic Gene Ontology Description Generation. 1060-1068 - Gang Liu, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Graph Rationalization with Environment-based Augmentations. 1069-1078 - Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Junjie Sun, Hong Yu, Xianchao Zhang:
Label-enhanced Prototypical Network with Contrastive Learning for Multi-label Few-shot Aspect Category Detection. 1079-1087 - Ji Liu, Zenan Li, Yuan Yao, Feng Xu, Xiaoxing Ma, Miao Xu, Hanghang Tong:
Fair Representation Learning: An Alternative to Mutual Information. 1088-1097 - Lihui Liu, Boxin Du, Jiejun Xu, Yinglong Xia, Hanghang Tong:
Joint Knowledge Graph Completion and Question Answering. 1098-1108 - Qu Liu, Tingjian Ge:
RL2: A Call for Simultaneous Representation Learning and Rule Learning for Graph Streams. 1109-1119 - Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang:
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries. 1120-1130 - Yang Liu, Xiang Ao, Fuli Feng, Qing He:
UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs. 1131-1140 - Yaxu Liu, Jui-Nan Yen, Bo-Wen Yuan, Rundong Shi, Peng Yan, Chih-Jen Lin:
Practical Counterfactual Policy Learning for Top-K Recommendations. 1141-1151 - Bin Lu, Xiaoying Gan, Lina Yang, Weinan Zhang, Luoyi Fu, Xinbing Wang:
Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation. 1152-1161 - Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang:
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer. 1162-1172 - Yue Lu, Renjie Wu, Abdullah Mueen, Maria A. Zuluaga, Eamonn J. Keogh:
Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams. 1173-1182 - Shuang Luo, Yinchuan Li, Jiahui Li, Kun Kuang, Furui Liu, Yunfeng Shao, Chao Wu:
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning? 1183-1191 - Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian:
Learning Differential Operators for Interpretable Time Series Modeling. 1192-1201 - Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan:
Learning Causal Effects on Hypergraphs. 1202-1212 - Pingchuan Ma, Rui Ding, Haoyue Dai, Yuanyuan Jiang, Shuai Wang, Shi Han, Dongmei Zhang:
ML4S: Learning Causal Skeleton from Vicinal Graphs. 1213-1223 - Yu Ma, Zhining Liu, Chenyi Zhuang, Yize Tan, Yi Dong, Wenliang Zhong, Jinjie Gu:
Non-stationary Time-aware Kernelized Attention for Temporal Event Prediction. 1224-1232 - Yunshan Ma, Yingzhi He, An Zhang, Xiang Wang, Tat-Seng Chua:
CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation. 1233-1241 - Sarah Mameche, David Kaltenpoth, Jilles Vreeken:
Discovering Invariant and Changing Mechanisms from Data. 1242-1252 - Reid McIlroy-Young, Russell Wang, Siddhartha Sen, Jon M. Kleinberg, Ashton Anderson:
Learning Models of Individual Behavior in Chess. 1253-1263 - Yosuke Mizutani, Annie Staker, Blair D. Sullivan:
Minimizing Congestion for Balanced Dominators. 1264-1274 - Ali Montazeralghaem, James Allan:
Extracting Relevant Information from User's Utterances in Conversational Search and Recommendation. 1275-1283 - Gyoung S. Na, Chanyoung Park:
Nonlinearity Encoding for Extrapolation of Neural Networks. 1284-1294 - Changdae Oh, Heeji Won, Junhyuk So, Taero Kim, Yewon Kim, Hosik Choi, Kyungwoo Song:
Learning Fair Representation via Distributional Contrastive Disentanglement. 1295-1305 - Maya Okawa, Tomoharu Iwata:
Predicting Opinion Dynamics via Sociologically-Informed Neural Networks. 1306-1316 - Qiying Pan, Yifei Zhu:
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy. 1317-1326 - Xudong Pan, Yifan Yan, Mi Zhang, Min Yang:
MetaV: A Meta-Verifier Approach to Task-Agnostic Model Fingerprinting. 1327-1336 - Marios Papachristou, Jon M. Kleinberg:
Core-periphery Models for Hypergraphs. 1337-1347 - Shuai Peng, Di Fu, Yong Cao, Yijun Liang, Gu Xu, Liangcai Gao, Zhi Tang:
Compute Like Humans: Interpretable Step-by-step Symbolic Computation with Deep Neural Network. 1348-1357 - Xiong Peng, Feng Liu, Jingfeng Zhang, Long Lan, Junjie Ye, Tongliang Liu, Bo Han:
Bilateral Dependency Optimization: Defending Against Model-inversion Attacks. 1358-1367 - Yifan Qi, Weiguo Zheng, Liang Hong, Lei Zou:
Evaluating Knowledge Graph Accuracy Powered by Optimized Human-machine Collaboration. 1368-1378 - Yunzhe Qi, Yikun Ban, Jingrui He:
Neural Bandit with Arm Group Graph. 1379-1389 - Yiyue Qian, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang:
Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning. 1390-1400 - Can Qin, Sungchul Kim, Handong Zhao, Tong Yu, Ryan A. Rossi, Yun Fu:
External Knowledge Infusion for Tabular Pre-training Models with Dual-adapters. 1401-1409 - Yuan Qiu, Wei Dong, Ke Yi, Bin Wu, Feifei Li:
Releasing Private Data for Numerical Queries. 1410-1419 - Xinghua Qu, Yew Soon Ong, Abhishek Gupta, Pengfei Wei, Zhu Sun, Zejun Ma:
Importance Prioritized Policy Distillation. 1420-1429 - Xinghua Qu, Pengfei Wei, Mingyong Gao, Zhu Sun, Yew Soon Ong, Zejun Ma:
Synthesising Audio Adversarial Examples for Automatic Speech Recognition. 1430-1440 - Zhongnan Qu, Zimu Zhou, Yongxin Tong, Lothar Thiele:
p-Meta: Towards On-device Deep Model Adaptation. 1441-1451 - Md. Mahmudur Rahman, Sanjay Purushotham:
Fair and Interpretable Models for Survival Analysis. 1452-1462 - Xuan Rao, Lisi Chen, Yong Liu, Shuo Shang, Bin Yao, Peng Han:
Graph-Flashback Network for Next Location Recommendation. 1463-1471 - Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans:
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. 1472-1482 - Qibing Ren, Yiting Chen, Yichuan Mo, Qitian Wu, Junchi Yan:
DICE: Domain-attack Invariant Causal Learning for Improved Data Privacy Protection and Adversarial Robustness. 1483-1492 - Shaogang Ren, Belhal Karimi, Dingcheng Li, Ping Li:
Variational Flow Graphical Model. 1493-1503 - Weijieying Ren, Pengyang Wang, Xiaolin Li, Charles E. Hughes, Yanjie Fu:
Semi-supervised Drifted Stream Learning with Short Lookback. 1504-1513 - Yuta Saito, Thorsten Joachims:
Fair Ranking as Fair Division: Impact-Based Individual Fairness in Ranking. 1514-1524 - Tomoya Sakai:
A Generalized Backward Compatibility Metric. 1525-1535 - Hitesh Sapkota, Qi Yu:
Balancing Bias and Variance for Active Weakly Supervised Learning. 1536-1546 - Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczynski:
On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification. 1547-1557 - Jie-Jing Shao, Yunlu Xu, Zhanzhan Cheng, Yufeng Li:
Active Model Adaptation Under Unknown Shift. 1558-1566 - Zezhi Shao, Zhao Zhang, Fei Wang, Yongjun Xu:
Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting. 1567-1577 - Wei Shen, Yang Yang, Yinan Liu:
Multi-View Clustering for Open Knowledge Base Canonicalization. 1578-1588 - Ge Shi, Jason Smucny, Ian Davidson:
Deep Learning for Prognosis Using Task-fMRI: A Novel Architecture and Training Scheme. 1589-1597 - Weili Shi, Ronghang Zhu, Sheng Li:
Pairwise Adversarial Training for Unsupervised Class-imbalanced Domain Adaptation. 1598-1606 - Zijian Shi, John Cartlidge:
State Dependent Parallel Neural Hawkes Process for Limit Order Book Event Stream Prediction and Simulation. 1607-1615 - Hyunwoo Sohn, Baekkwan Park:
Robust and Informative Text Augmentation (RITA) via Constrained Worst-Case Transformations for Low-Resource Named Entity Recognition. 1616-1624 - Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li:
GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks. 1625-1634 - Yu Song, Donglin Wang:
Learning on Graphs with Out-of-Distribution Nodes. 1635-1645 - Yuanfeng Song, Xuefang Zhao, Raymond Chi-Wing Wong, Di Jiang:
RGVisNet: A Hybrid Retrieval-Generation Neural Framework Towards Automatic Data Visualization Generation. 1646-1655 - Zixing Song, Yifei Zhang, Irwin King:
Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification. 1656-1665 - Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong:
ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. 1666-1675 - Yixin Su, Yunxiang Zhao, Sarah M. Erfani, Junhao Gan, Rui Zhang:
Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems. 1676-1686 - Zhan Su, Zhicheng Dou, Yutao Zhu, Ji-Rong Wen:
Knowledge Enhanced Search Result Diversification. 1687-1695 - Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua:
Causal Attention for Interpretable and Generalizable Graph Classification. 1696-1705 - Jianhui Sun, Mengdi Huai, Kishlay Jha, Aidong Zhang:
Demystify Hyperparameters for Stochastic Optimization with Transferable Representations. 1706-1716 - Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang:
GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks. 1717-1727 - Xingzhi Sun, Ziyu Wang, Rui Ding, Shi Han, Dongmei Zhang:
pureGAM: Learning an Inherently Pure Additive Model. 1728-1738 - Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuki Yamanaka, Hisashi Kashima:
Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders. 1739-1748 - Suhas Thejaswi, Ameet Gadekar, Bruno Ordozgoiti, Michal Osadnik:
Clustering with Fair-Center Representation: Parameterized Approximation Algorithms and Heuristics. 1749-1759 - Shiwei Tong, Jiayu Liu, Yuting Hong, Zhenya Huang, Le Wu, Qi Liu, Wei Huang, Enhong Chen, Dan Zhang:
Incremental Cognitive Diagnosis for Intelligent Education. 1760-1770 - Christopher Tran, Elena Zheleva:
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty. 1787-1797 - Nhu-Thuat Tran, Hady W. Lauw:
Aligning Dual Disentangled User Representations from Ratings and Textual Content. 1798-1806 - Thomas J. Vandal, Kate Duffy, Will McCarty, Akira Sewnath, Ramakrishna R. Nemani:
Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow. 1807-1815 - Chenyang Wang, Yuanqing Yu, Weizhi Ma, Min Zhang, Chong Chen, Yiqun Liu, Shaoping Ma:
Towards Representation Alignment and Uniformity in Collaborative Filtering. 1816-1825 - Dongjie Wang, Yanjie Fu, Kunpeng Liu, Xiaolin Li, Yan Solihin:
Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction. 1826-1834 - Han Wang, Jayashree Sharma, Shuya Feng, Kai Shu, Yuan Hong:
A Model-Agnostic Approach to Differentially Private Topic Mining. 1835-1845 - Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. 1846-1856 - Haotian Wang, Wenjing Yang, Longqi Yang, Anpeng Wu, Liyang Xu, Jing Ren, Fei Wu, Kun Kuang:
Estimating Individualized Causal Effect with Confounded Instruments. 1857-1867 - Jiayin Wang, Weizhi Ma, Jiayu Li, Hongyu Lu, Min Zhang, Biao Li, Yiqun Liu, Peng Jiang, Shaoping Ma:
Make Fairness More Fair: Fair Item Utility Estimation and Exposure Re-Distribution. 1868-1877 - Junshan Wang, Wenhao Zhu, Guojie Song, Liang Wang:
Streaming Graph Neural Networks with Generative Replay. 1878-1888 - Lihan Wang, Bowen Qin, Binyuan Hui, Bowen Li, Min Yang, Bailin Wang, Binhua Li, Jian Sun, Fei Huang, Luo Si, Yongbin Li:
Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing. 1889-1898 - Minrui Wang, Mingxiao Feng, Wengang Zhou, Houqiang Li:
Stabilizing Voltage in Power Distribution Networks via Multi-Agent Reinforcement Learning with Transformer. 1899-1909 - Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li:
Task-Adaptive Few-shot Node Classification. 1910-1919 - Wei Wang, Min-Ling Zhang:
Partial Label Learning with Discrimination Augmentation. 1920-1928 - Xiaolei Wang, Kun Zhou, Ji-Rong Wen, Wayne Xin Zhao:
Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning. 1929-1937 - Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr:
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage. 1938-1948 - Zhen Wang, Zhewei Wei, Yaliang Li, Weirui Kuang, Bolin Ding:
Graph Neural Networks with Node-wise Architecture. 1949-1958 - Zihan Wang, Na Huang, Fei Sun, Pengjie Ren, Zhumin Chen, Hengliang Luo, Maarten de Rijke, Zhaochun Ren:
Debiasing Learning for Membership Inference Attacks Against Recommender Systems. 1959-1968 - Zimu Wang, Yue He, Jiashuo Liu, Wenchao Zou, Philip S. Yu, Peng Cui:
Invariant Preference Learning for General Debiasing in Recommendation. 1969-1978 - Jiawen Wei, Fangyuan Wang, Wanxin Zeng, Wenwei Lin, Ning Gui:
An Embedded Feature Selection Framework for Control. 1979-1988 - Tianxin Wei, Jingrui He:
Comprehensive Fair Meta-learned Recommender System. 1989-1999 - Ying Wei, Qi Li:
SagDRE: Sequence-Aware Graph-Based Document-Level Relation Extraction with Adaptive Margin Loss. 2000-2008 - Qianlong Wen, Zhongyu Ouyang, Jianfei Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang:
Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction. 2009-2019 - Tyler Wilson, Andrew McDonald, Asadullah Hill Galib, Pang-Ning Tan, Lifeng Luo:
Beyond Point Prediction: Capturing Zero-Inflated & Heavy-Tailed Spatiotemporal Data with Deep Extreme Mixture Models. 2020-2028 - Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu:
Multi-fidelity Hierarchical Neural Processes. 2029-2038 - Jun Wu, Jingrui He:
Domain Adaptation with Dynamic Open-Set Targets. 2039-2049 - Kailun Wu, Weijie Bian, Zhangming Chan, Lejian Ren, Shiming Xiang, Shuguang Han, Hongbo Deng, Bo Zheng:
Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction. 2050-2058 - Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Caihua Shan, Yiheng Sun, Yangyong Zhu, Philip S. Yu:
CLARE: A Semi-supervised Community Detection Algorithm. 2059-2069 - Yue Wu, Jesús A. De Loera:
Geometric Policy Iteration for Markov Decision Processes. 2070-2078 - Yuhang Wu, Zeyu Zheng, Guangyu Zhang, Zuohua Zhang, Chu Wang:
Non-stationary A/B Tests. 2079-2089 - Zhebin Wu, Lin Shu, Ziyue Xu, Yaomin Chang, Chuan Chen, Zibin Zheng:
Robust Tensor Graph Convolutional Networks via T-SVD based Graph Augmentation. 2090-2099 - Lianghao Xia, Chao Huang, Chuxu Zhang:
Self-Supervised Hypergraph Transformer for Recommender Systems. 2100-2109 - Xiaobo Xia, Shuo Shan, Mingming Gong, Nannan Wang, Fei Gao, Haikun Wei, Tongliang Liu:
Sample-Efficient Kernel Mean Estimator with Marginalized Corrupted Data. 2110-2119 - Shufang Xie, Rui Yan, Peng Han, Yingce Xia, Lijun Wu, Chenjuan Guo, Bin Yang, Tao Qin:
RetroGraph: Retrosynthetic Planning with Graph Search. 2120-2129 - Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, Steffen Staab:
Ultrahyperbolic Knowledge Graph Embeddings. 2130-2139 - Ziran Xiong, Wanli Shi, Bin Gu:
End-to-End Semi-Supervised Ordinal Regression AUC Maximization with Convolutional Kernel Networks. 2140-2150 - Yuan Xu, Jiajie Xu, Jing Zhao, Kai Zheng, An Liu, Lei Zhao, Xiaofang Zhou:
MetaPTP: An Adaptive Meta-optimized Model for Personalized Spatial Trajectory Prediction. 2151-2159 - Ge Yan, Yehui Tang, Junchi Yan:
Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach. 2160-2168 - Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang:
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach. 2169-2179 - Yikai Yan, Chaoyue Niu, Renjie Gu, Fan Wu, Shaojie Tang, Lifeng Hua, Chengfei Lyu, Guihai Chen:
On-Device Learning for Model Personalization with Large-Scale Cloud-Coordinated Domain Adaption. 2180-2190 - Chen-Hsu Yang, Chih-Ya Shen:
Enhancing Machine Learning Approaches for Graph Optimization Problems with Diversifying Graph Augmentation. 2191-2201 - Jing Yang, Kai Xie, Ning An:
Causal Discovery on Non-Euclidean Data. 2202-2211 - Menglin Yang, Zhihao Li, Min Zhou, Jiahong Liu, Irwin King:
HICF: Hyperbolic Informative Collaborative Filtering. 2212-2221 - Puhai Yang, Heyan Huang, Wei Wei, Xian-Ling Mao:
Toward Real-life Dialogue State Tracking Involving Negative Feedback Utterances. 2222-2232 - Qingping Yang, Yixuan Cao, Ping Luo:
Numerical Tuple Extraction from Tables with Pre-training. 2233-2241 - Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu:
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions. 2242-2252 - Ruichao Yang, Xiting Wang, Yiqiao Jin, Chaozhuo Li, Jianxun Lian, Xing Xie:
Reinforcement Subgraph Reasoning for Fake News Detection. 2253-2262 - Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li:
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation. 2263-2274 - Di Yao, Haonan Hu, Lun Du, Gao Cong, Shi Han, Jingping Bi:
TrajGAT: A Graph-based Long-term Dependency Modeling Approach for Trajectory Similarity Computation. 2275-2285 - Shota Yasui, Masahiro Kato:
Learning Classifiers under Delayed Feedback with a Time Window Assumption. 2286-2295 - Junchen Ye, Zihan Liu, Bowen Du, Leilei Sun, Weimiao Li, Yanjie Fu, Hui Xiong:
Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting. 2296-2306 - Muchao Ye, Jinghui Chen, Chenglin Miao, Ting Wang, Fenglong Ma:
LeapAttack: Hard-Label Adversarial Attack on Text via Gradient-Based Optimization. 2307-2315 - Changchang Yin, Ruoqi Liu, Jeffrey M. Caterino, Ping Zhang:
Deconfounding Actor-Critic Network with Policy Adaptation for Dynamic Treatment Regimes. 2316-2326 - Chunxing Yin, Da Zheng, Israt Nisa, Christos Faloutsos, George Karypis, Richard W. Vuduc:
Nimble GNN Embedding with Tensor-Train Decomposition. 2327-2335 - Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, U Kang:
Accurate Node Feature Estimation with Structured Variational Graph Autoencoder. 2336-2346 - Susik Yoon, Youngjun Lee, Jae-Gil Lee, Byung Suk Lee:
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream. 2347-2357 - Jiaxuan You, Tianyu Du, Jure Leskovec:
ROLAND: Graph Learning Framework for Dynamic Graphs. 2358-2366 - Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Availability Attacks Create Shortcuts. 2367-2376 - Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong:
Multiplex Heterogeneous Graph Convolutional Network. 2377-2387 - Sizhe Yu, Ziyi Liu, Shixiang Wan, Jia Zheng, Zang Li, Fan Zhou:
MDP2 Forest: A Constrained Continuous Multi-dimensional Policy Optimization Approach for Short-video Recommendation. 2388-2398 - Jingyi Yuan, Yang Weng, Erik Blasch:
Intrinsic-Motivated Sensor Management: Exploring with Physical Surprise. 2399-2407 - Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai:
Dual Bidirectional Graph Convolutional Networks for Zero-shot Node Classification. 2408-2417 - Chaohe Zhang, Xu Chu, Liantao Ma, Yinghao Zhu, Yasha Wang, Jiangtao Wang, Junfeng Zhao:
M3Care: Learning with Missing Modalities in Multimodal Healthcare Data. 2418-2428 - Delvin Ce Zhang, Hady Wirawan Lauw:
Variational Graph Author Topic Modeling. 2429-2438 - Guozhen Zhang, Zihan Yu, Depeng Jin, Yong Li:
Physics-infused Machine Learning for Crowd Simulation. 2439-2449 - Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang:
Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer. 2450-2460 - Shaofeng Zhang, Meng Liu, Junchi Yan, Hengrui Zhang, Lingxiao Huang, Xiaokang Yang, Pinyan Lu:
M-Mix: Generating Hard Negatives via Multi-sample Mixing for Contrastive Learning. 2461-2470 - Weijia Zhang, Hao Liu, Jindong Han, Yong Ge, Hui Xiong:
Multi-Agent Graph Convolutional Reinforcement Learning for Dynamic Electric Vehicle Charging Pricing. 2471-2481 - Weiyu Zhang, Yiyang Ma, Di Zhu, Lei Dong, Yu Liu:
MetroGAN: Simulating Urban Morphology with Generative Adversarial Network. 2482-2492 - Wentao Zhang, Zeang Sheng, Ziqi Yin, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui:
Model Degradation Hinders Deep Graph Neural Networks. 2493-2503 - Xiao Zhang, Sunhao Dai, Jun Xu, Zhenhua Dong, Quanyu Dai, Ji-Rong Wen:
Counteracting User Attention Bias in Music Streaming Recommendation via Reward Modification. 2504-2514 - Yanfu Zhang, Shangqian Gao, Jian Pei, Heng Huang:
Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks. 2515-2523 - Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King:
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning. 2524-2534 - Yunyi Zhang, Fang Guo, Jiaming Shen, Jiawei Han:
Unsupervised Key Event Detection from Massive Text Corpora. 2535-2544 - Zaixi Zhang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong:
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients. 2545-2555 - Zhen-Yu Zhang, Yuyang Qian, Yu-Jie Zhang, Yuan Jiang, Zhi-Hua Zhou:
Adaptive Learning for Weakly Labeled Streams. 2556-2564 - Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen:
Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. 2565-2575 - Ruijie Zhao, Xianwen Deng, Zhicong Yan, Jun Ma, Zhi Xue, Yijun Wang:
MT-FlowFormer: A Semi-Supervised Flow Transformer for Encrypted Traffic Classification. 2576-2584 - Weijie Zhao, Yingjie Lao, Ping Li:
Integrity Authentication in Tree Models. 2585-2593 - Lecheng Zheng, Jinjun Xiong, Yada Zhu, Jingrui He:
Contrastive Learning with Complex Heterogeneity. 2594-2604 - Yanping Zheng, Hanzhi Wang, Zhewei Wei, Jiajun Liu, Sibo Wang:
Instant Graph Neural Networks for Dynamic Graphs. 2605-2615 - Zihan Zhou, Zijia Du, Somali Chaterji:
KRATOS: Context-Aware Cell Type Classification and Interpretation using Joint Dimensionality Reduction and Clustering. 2616-2625 - Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Unified 2D and 3D Pre-Training of Molecular Representations. 2626-2636 - Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra:
How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications. 2637-2647 - Liwang Zhu, Zhongzhi Zhang:
A Nearly-Linear Time Algorithm for Minimizing Risk of Conflict in Social Networks. 2648-2656
ADS Track Papers
- Prerna Agarwal, Buyu Gao, Siyu Huo, Prabhat Reddy, Sampath Dechu, Yazan Obeidi, Vinod Muthusamy, Vatche Isahagian, Sebastian Carbajales:
A Process-Aware Decision Support System for Business Processes. 2673-2681 - Azza H. Ahmed, Michael A. Riegler, Steven Alexander Hicks, Ahmed Elmokashfi:
RCAD: Real-time Collaborative Anomaly Detection System for Mobile Broadband Networks. 2682-2691 - Mohammad Amini, Zhanguang Zhang, Surya Penmetsa, Yingxue Zhang, Jianye Hao, Wulong Liu:
Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding. 2692-2702 - Paul Baltescu, Haoyu Chen, Nikil Pancha, Andrew Zhai, Jure Leskovec, Charles Rosenberg:
ItemSage: Learning Product Embeddings for Shopping Recommendations at Pinterest. 2703-2711 - Wendong Bi, Bingbing Xu, Xiaoqian Sun, Zidong Wang, Huawei Shen, Xueqi Cheng:
Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks. 2712-2720 - Changyu Chen, Xiting Wang, Xiaoyuan Yi, Fangzhao Wu, Xing Xie, Rui Yan:
Personalized Chit-Chat Generation for Recommendation Using External Chat Corpora. 2721-2731 - Chi Chen, Hui Chen, Kangzhi Zhao, Junsheng Zhou, Li He, Hongbo Deng, Jian Xu, Bo Zheng, Yong Zhang, Chunxiao Xing:
EXTR: Click-Through Rate Prediction with Externalities in E-Commerce Sponsored Search. 2732-2740 - Junru Chen, Yang Yang, Tao Yu, Yingying Fan, Xiaolong Mo, Carl Yang:
BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning. 2741-2751 - Shengyu Chen, Jacob A. Zwart, Xiaowei Jia:
Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks. 2752-2761 - Tianyi Chen, Charalampos E. Tsourakakis:
AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks. 2762-2770 - Zebin Chen, Xiaolin Xiao, Yue-Jiao Gong, Jun Fang, Nan Ma, Hua Chai, Zhiguang Cao:
Interpreting Trajectories from Multiple Views: A Hierarchical Self-Attention Network for Estimating the Time of Arrival. 2771-2779 - Gopinath Chennupati, Milind Rao, Gurpreet Chadha, Aaron Eakin, Anirudh Raju, Gautam Tiwari, Anit Kumar Sahu, Ariya Rastrow, Jasha Droppo, Andy Oberlin, Buddha Nandanoor, Prahalad Venkataramanan, Zheng Wu, Pankaj Sitpure:
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale. 2780-2788 - Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Chandan K. Reddy:
Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance. 2789-2799 - Shih-Chieh Dai, Yi-Li Hsu, Aiping Xiong, Lun-Wei Ku:
Ask to Know More: Generating Counterfactual Explanations for Fake Claims. 2800-2810 - Orit Davidovich, Gheorghe-Teodor Bercea, Segev Wasserkrug:
The Good, the Bad, and the Outliers: A Testing Framework for Decision Optimization Model Learning. 2811-2821 - Ming Du, Arnau Ramisa, Amit Kumar K. C, Sampath Chanda, Mengjiao Wang, Neelakandan Rajesh, Shasha Li, Yingchuan Hu, Tao Zhou, Nagashri Lakshminarayana, Son Tran, Doug Gray:
Amazon Shop the Look: A Visual Search System for Fashion and Home. 2822-2830 - Jane Dwivedi-Yu, Yi-Chia Wang, Lijing Qin, Cristian Canton-Ferrer, Alon Y. Halevy:
Affective Signals in a Social Media Recommender System. 2831-2841 - Ahmed El-Kishky, Thomas Markovich, Serim Park, Chetan Verma, Baekjin Kim, Ramy Eskander, Yury Malkov, Frank Portman, Sofía Samaniego, Ying Xiao, Aria Haghighi:
TwHIN: Embedding the Twitter Heterogeneous Information Network for Personalized Recommendation. 2842-2850 - Xiaochuan Fan, Chi Zhang, Yong Yang, Yue Shang, Xueying Zhang, Zhen He, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Generation of Product-Image Sequence in E-commerce. 2851-2859 - Majid Farhadloo, Carl Molnar, Gaoxiang Luo, Yan Li, Shashi Shekhar, Rachel L. Maus, Svetomir N. Markovic, Alexey A. Leontovich, Raymond Moore:
SAMCNet: Towards a Spatially Explainable AI Approach for Classifying MxIF Oncology Data. 2860-2870 - Dennis Fedorishin, Justas Birgiolas, Deen Dayal Mohan, Livio Forte, Philip Schneider, Srirangaraj Setlur, Venu Govindaraju:
Large-Scale Acoustic Automobile Fault Detection: Diagnosing Engines Through Sound. 2871-2881 - Tao Feng, Tong Xia, Xiaochen Fan, Huandong Wang, Zefang Zong, Yong Li:
Precise Mobility Intervention for Epidemic Control Using Unobservable Information via Deep Reinforcement Learning. 2882-2892 - Jack FitzGerald, Shankar Ananthakrishnan, Konstantine Arkoudas, Davide Bernardi, Abhishek Bhagia, Claudio Delli Bovi, Jin Cao, Rakesh Chada, Amit Chauhan, Luoxin Chen, Anurag Dwarakanath, Satyam Dwivedi, Turan Gojayev, Karthik Gopalakrishnan, Thomas Gueudré, Dilek Hakkani-Tur, Wael Hamza, Jonathan J. Hüser, Kevin Martin Jose, Haidar Khan, Beiye Liu, Jianhua Lu, Alessandro Manzotti, Pradeep Natarajan, Karolina Owczarzak, Gokmen Oz, Enrico Palumbo, Charith Peris, Chandana Satya Prakash, Stephen Rawls, Andy Rosenbaum, Anjali Shenoy, Saleh Soltan, Mukund Harakere Sridhar, Lizhen Tan, Fabian Triefenbach, Pan Wei, Haiyang Yu, Shuai Zheng, Gökhan Tür, Prem Natarajan:
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems. 2893-2902 - Alex Foo, Wynne Hsu, Mong-Li Lee, Gavin Siew Wei Tan:
DP-GAT: A Framework for Image-based Disease Progression Prediction. 2903-2912 - Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. 2913-2923 - Chengliang Gao, Fan Zhang, Yue Zhou, Ronggen Feng, Qiang Ru, Kaigui Bian, Renqing He, Zhizhao Sun:
Applying Deep Learning Based Probabilistic Forecasting to Food Preparation Time for On-Demand Delivery Service. 2924-2934 - Jiannan Guo, Yangyang Kang, Yu Duan, Xiaozhong Liu, Siliang Tang, Wenqiao Zhang, Kun Kuang, Changlong Sun, Fei Wu:
Collaborative Intelligence Orchestration: Inconsistency-Based Fusion of Semi-Supervised Learning and Active Learning. 2935-2945 - Xiaojie Guo, Qingkai Zeng, Meng Jiang, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Controllable Product Copywriting for E-Commerce. 2946-2956 - Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong:
Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning. 2957-2967 - Benjamin Han, Hyungjun Lee, Sébastien Martin:
Real-Time Rideshare Driver Supply Values Using Online Reinforcement Learning. 2968-2976 - Siho Han, Simon S. Woo:
Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series. 2977-2986 - Shiqi Hao, Yang Liu, Yu Wang, Yuan Wang, Wenming Zhe:
Three-Stage Root Cause Analysis for Logistics Time Efficiency via Explainable Machine Learning. 2987-2996 - Zhicheng He, Wei Xia, Kai Dong, Huifeng Guo, Ruiming Tang, Dingyin Xia, Rui Zhang:
Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms. 2997-3006 - Reza Hosseini, Albert Chen, Kaixu Yang, Sayan Patra, Yi Su, Saad Eddin Al Orjany, Sishi Tang, Parvez Ahammad:
Greykite: Deploying Flexible Forecasting at Scale at LinkedIn. 3007-3017 - Weihua Hu, Rajas Bansal, Kaidi Cao, Nikhil Rao, Karthik Subbian, Jure Leskovec:
Learning Backward Compatible Embeddings. 3018-3028 - Jizhou Huang, Haifeng Wang, Yibo Sun, Yunsheng Shi, Zhengjie Huang, An Zhuo, Shikun Feng:
ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps. 3029-3039 - Jizhou Huang, Haifeng Wang, Shiqiang Ding, Shaolei Wang:
DuIVA: An Intelligent Voice Assistant for Hands-free and Eyes-free Voice Interaction with the Baidu Maps App. 3040-3050 - Rolf Jagerman, Xuanhui Wang, Honglei Zhuang, Zhen Qin, Michael Bendersky, Marc Najork:
Rax: Composable Learning-to-Rank Using JAX. 3051-3060 - Nikita Janakarajan, Jannis Born, Matteo Manica:
A Fully Differentiable Set Autoencoder. 3061-3071 - Jiahao Ji, Jingyuan Wang, Junjie Wu, Boyang Han, Junbo Zhang, Yu Zheng:
Precision CityShield Against Hazardous Chemicals Threats via Location Mining and Self-Supervised Learning. 3072-3080 - Tong Jia, Ying Li, Yong Yang, Gang Huang, Zhonghai Wu:
Augmenting Log-based Anomaly Detection Models to Reduce False Anomalies with Human Feedback. 3081-3089 - Yiren Jian, Erik Kruus, Martin Renqiang Min:
T-Cell Receptor-Peptide Interaction Prediction with Physical Model Augmented Pseudo-Labeling. 3090-3097 - Jiawei Jiang, Yusong Hu, Xiaosen Li, Wen Ouyang, Zhitao Wang, Fangcheng Fu, Bin Cui:
Analyzing Online Transaction Networks with Network Motifs. 3098-3106 - Dovile Juodelyte, Veronika Cheplygina, Therese Graversen, Philippe Bonnet:
Predicting Bearings Degradation Stages for Predictive Maintenance in the Pharmaceutical Industry. 3107-3115 - Jean-François Kagy, Flip Korn, Afshin Rostamizadeh, Chris Welty:
Vexation-Aware Active Learning for On-Menu Restaurant Dish Availability. 3116-3126 - Yashal Shakti Kanungo, Gyanendra Das, Pooja A, Sumit Negi:
COBART: Controlled, Optimized, Bidirectional and Auto-Regressive Transformer for Ad Headline Generation. 3127-3136 - Sudipta Kar, Giuseppe Castellucci, Simone Filice, Shervin Malmasi, Oleg Rokhlenko:
Preventing Catastrophic Forgetting in Continual Learning of New Natural Language Tasks. 3137-3145 - Hyunsung Kim, Bit Kim, Dongwook Chung, Jinsung Yoon, Sang-Ki Ko:
SoccerCPD: Formation and Role Change-Point Detection in Soccer Matches Using Spatiotemporal Tracking Data. 3146-3156 - Tasuku Kimura, Yasuko Matsubara, Koki Kawabata, Yasushi Sakurai:
Fast Mining and Forecasting of Co-evolving Epidemiological Data Streams. 3157-3167 - Ron Kohavi, Alex Deng, Lukas Vermeer:
A/B Testing Intuition Busters: Common Misunderstandings in Online Controlled Experiments. 3168-3177 - Weize Kong, Swaraj Khadanga, Cheng Li, Shaleen Kumar Gupta, Mingyang Zhang, Wensong Xu, Michael Bendersky:
Multi-Aspect Dense Retrieval. 3178-3186 - Xiaoyu Kou, Tianqi Zhao, Fan Zhang, Song Li, Qi Zhang:
Self-Supervised Augmentation and Generation for Multi-lingual Text Advertisements at Bing. 3187-3196 - Alyssa Lees, Vinh Q. Tran, Yi Tay, Jeffrey Sorensen, Jai Prakash Gupta, Donald Metzler, Lucy Vasserman:
A New Generation of Perspective API: Efficient Multilingual Character-level Transformers. 3197-3207 - Bo Li, Qiang He, Liang Yuan, Feifei Chen, Lingjuan Lyu, Yun Yang:
EdgeWatch: Collaborative Investigation of Data Integrity at the Edge based on Blockchain. 3208-3218 - Hui Li, Xing Fu, Ruofan Wu, Jinyu Xu, Kai Xiao, Xiaofu Chang, Weiqiang Wang, Shuai Chen, Leilei Shi, Tao Xiong, Yuan Qi:
Design Domain Specific Neural Network via Symbolic Testing. 3219-3229 - Mingjie Li, Zeyan Li, Kanglin Yin, Xiaohui Nie, Wenchi Zhang, Kaixin Sui, Dan Pei:
Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention Recognition. 3230-3240 - Xiang Li, Xiaojiang Zhou, Yao Xiao, Peihao Huang, Dayao Chen, Sheng Chen, Yunsen Xian:
AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System. 3241-3249 - Xu Li, Michelle Ma Zhang, Zhenya Wang, Youjun Tong:
Arbitrary Distribution Modeling with Censorship in Real-Time Bidding Advertising. 3250-3258 - Yinfeng Li, Chen Gao, Xiaoyi Du, Huazhou Wei, Hengliang Luo, Depeng Jin, Yong Li:
Automatically Discovering User Consumption Intents in Meituan. 3259-3269 - Yuening Li, Zhengzhang Chen, Daochen Zha, Mengnan Du, Jingchao Ni, Denghui Zhang, Haifeng Chen, Xia Hu:
Towards Learning Disentangled Representations for Time Series. 3270-3278 - Zhuliu Li, Yiming Wang, Xiao Yan, Weizhi Meng, Yanen Li, Jaewon Yang:
TaxoTrans: Taxonomy-Guided Entity Translation. 3279-3287 - Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu:
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. 3288-3298 - Ting-En Lin, Yuchuan Wu, Fei Huang, Luo Si, Jian Sun, Yongbin Li:
Duplex Conversation: Towards Human-like Interaction in Spoken Dialogue Systems. 3299-3308 - Weilin Lin, Xiangyu Zhao, Yejing Wang, Tong Xu, Xian Wu:
AdaFS: Adaptive Feature Selection in Deep Recommender System. 3309-3317 - Xiexiong Lin, Huaisong Li, Tao Huang, Feng Wang, Linlin Chao, Fuzhen Zhuang, Taifeng Wang, Tianyi Zhang:
A Logic Aware Neural Generation Method for Explainable Data-to-text. 3318-3326 - Zihan Lin, Hui Wang, Jingshu Mao, Wayne Xin Zhao, Cheng Wang, Peng Jiang, Ji-Rong Wen:
Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation. 3327-3335 - Michael Lindon, Chris Sanden, Vaché Shirikian:
Rapid Regression Detection in Software Deployments through Sequential Testing. 3336-3346 - Bulou Liu, Bing Bai, Weibang Xie, Yiwen Guo, Hao Chen:
Task-optimized User Clustering based on Mobile App Usage for Cold-start Recommendations. 3347-3356 - Can Liu, Yuncong Gao, Li Sun, Jinghua Feng, Hao Yang, Xiang Ao:
User Behavior Pre-training for Online Fraud Detection. 3357-3365 - Chang Liu, Chen Gao, Yuan Yuan, Chen Bai, Lingrui Luo, Xiaoyi Du, Xinlei Shi, Hengliang Luo, Depeng Jin, Yong Li:
Modeling Persuasion Factor of User Decision for Recommendation. 3366-3376 - Hanyang Liu, Sunny S. Lou, Benjamin C. Warner, Derek R. Harford, Thomas George Kannampallil, Chenyang Lu:
HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records. 3377-3387 - Hao Liu, Qian Gao, Xiaochao Liao, Guangxing Chen, Hao Xiong, Silin Ren, Guobao Yang, Zhiwei Zha:
Lion: A GPU-Accelerated Online Serving System for Web-Scale Recommendation at Baidu. 3388-3397 - Ruixuan Liu, Fangzhao Wu, Chuhan Wu, Yanlin Wang, Lingjuan Lyu, Hong Chen, Xing Xie:
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices. 3398-3406 - Wei Liu, Yi Ding, Shuai Wang, Yu Yang, Desheng Zhang:
Para-Pred: Addressing Heterogeneity for City-Wide Indoor Status Estimation in On-Demand Delivery. 3407-3417 - Xiao Liu, Da Yin, Jingnan Zheng, Xingjian Zhang, Peng Zhang, Hongxia Yang, Yuxiao Dong, Jie Tang:
OAG-BERT: Towards a Unified Backbone Language Model for Academic Knowledge Services. 3418-3428 - Xinyi Liu, Wanxian Guan, Lianyun Li, Hui Li, Chen Lin, Xubin Li, Si Chen, Jian Xu, Hongbo Deng, Bo Zheng:
Pretraining Representations of Multi-modal Multi-query E-commerce Search. 3429-3437 - Yudong Liu, Hailan Yang, Pu Zhao, Minghua Ma, Chengwu Wen, Hongyu Zhang, Chuan Luo, Qingwei Lin, Chang Yi, Jiaojian Wang, Chenjian Zhang, Paul Wang, Yingnong Dang, Saravan Rajmohan, Dongmei Zhang:
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems. 3438-3446 - Eleanor Loh, Jalaj Khandelwal, Brian Regan, Duncan A. Little:
Promotheus: An End-to-End Machine Learning Framework for Optimizing Markdown in Online Fashion E-commerce. 3447-3457 - Yunfei Lu, Peng Cui, Linyun Yu, Lei Li, Wenwu Zhu:
Uncovering the Heterogeneous Effects of Preference Diversity on User Activeness: A Dynamic Mixture Model. 3458-3467 - Handong Ma, Jiahang Cao, Yuchen Fang, Weinan Zhang, Wenbo Sheng, Shaodian Zhang, Yong Yu:
Retrieval-Based Gradient Boosting Decision Trees for Disease Risk Assessment. 3468-3476 - Ning Ma, Mustafa Ispir, Yuan Li, Yongpeng Yang, Zhe Chen, Derek Zhiyuan Cheng, Lan Nie, Kishor Barman:
An Online Multi-task Learning Framework for Google Feed Ads Auction Models. 3477-3485 - Yiming Ma:
CS-RAD: Conditional Member Status Refinement and Ability Discovery for Social Network Applications. 3486-3494 - Alessandro Magnani, Feng Liu, Suthee Chaidaroon, Sachin Yadav, Praveen Reddy Suram, Ajit Puthenputhussery, Sijie Chen, Min Xie, Anirudh Kashi, Tony Lee, Ciya Liao:
Semantic Retrieval at Walmart. 3495-3503 - Sourab Mangrulkar, Ankith M. S, Vivek Sembium:
BE3R: BERT based Early-Exit Using Expert Routing. 3504-3512 - Igor L. Markov, Hanson Wang, Nitya S. Kasturi, Shaun Singh, Mia R. Garrard, Yin Huang, Sze Wai Celeste Yuen, Sarah Tran, Zehui Wang, Igor Glotov, Tanvi Gupta, Peng Chen, Boshuang Huang, Xiaowen Xie, Michael Belkin, Sal Uryasev, Sam Howie, Eytan Bakshy, Norm Zhou:
Looper: An End-to-End ML Platform for Product Decisions. 3513-3523 - Sarah Masud, Manjot Bedi, Mohammad Aflah Khan, Md. Shad Akhtar, Tanmoy Chakraborty:
Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization. 3524-3534 - Yoshiki Matsune, Kota Tsubouchi, Nobuhiko Nishio:
CERAM: Coverage Expansion for Recommendations by Associating Discarded Models. 3535-3545 - Xuying Meng, Yequan Wang, Runxin Ma, Haitong Luo, Xiang Li, Yujun Zhang:
Packet Representation Learning for Traffic Classification. 3546-3554 - Seungwon Min, Kun Wu, Mert Hidayetoglu, Jinjun Xiong, Xiang Song, Wen-Mei Hwu:
Graph Neural Network Training and Data Tiering. 3555-3565 - François Mirallès, Luc Cauchon, Marc-André Magnan, François Grégoire, Mouhamadou Makhtar Dione, Arnaud Zinflou:
Towards Reliable Detection of Dielectric Hotspots in Thermal Images of the Underground Distribution Network. 3566-3574 - Roshanak Zilouchian Moghaddam, Spandan Garg, Colin B. Clement, Yevhen Mohylevskyy, Neel Sundaresan:
Generating Examples from CLI Usage: Can Transformers Help? 3575-3583 - Abhirup Mondal, Anirban Majumder, Vineet Chaoji:
ASPIRE: Air Shipping Recommendation for E-commerce Products via Causal Inference Framework. 3584-3592 - Fariha Moomtaheen, Matthew Killeen, James T. Oswald, Anna Gonzàlez-Rosell, Peter Mastracco, Alexander Gorovits, Stacy M. Copp, Petko Bogdanov:
DNA-Stabilized Silver Nanocluster Design via Regularized Variational Autoencoders. 3593-3602 - Han Cheol Moon, Shafiq R. Joty, Xu Chi:
GradMask: Gradient-Guided Token Masking for Textual Adversarial Example Detection. 3603-3613 - Anshuman Mourya, Prateek Sircar, Anirban Majumder, Deepak Gupta:
Solar: Science of Entity Loss Attribution. 3614-3622 - Marco Mussi, Gianmarco Genalti, Francesco Trovò, Alessandro Nuara, Nicola Gatti, Marcello Restelli:
Pricing the Long Tail by Explainable Product Aggregation and Monotonic Bandits. 3623-3633 - Chirag Nagpal, Mononito Goswami, Keith Dufendach, Artur Dubrawski:
Counterfactual Phenotyping with Censored Time-to-Events. 3634-3644 - Viet-An Nguyen, Peibei Shi, Jagdish Ramakrishnan, Narjes Torabi, Nimar S. Arora, Udi Weinsberg, Michael Tingley:
Crowdsourcing with Contextual Uncertainty. 3645-3655 - David Nigenda, Zohar Karnin, Muhammad Bilal Zafar, Raghu Ramesha, Alan Tan, Michele Donini, Krishnaram Kenthapadi:
Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models. 3671-3681 - Alexander V. Nikitin, Samuel Kaski:
Human-in-the-Loop Large-Scale Predictive Maintenance of Workstations. 3682-3690 - John Palowitch, Anton Tsitsulin, Brandon A. Mayer, Bryan Perozzi:
GraphWorld: Fake Graphs Bring Real Insights for GNNs. 3691-3701 - Nikil Pancha, Andrew Zhai, Jure Leskovec, Charles Rosenberg:
PinnerFormer: Sequence Modeling for User Representation at Pinterest. 3702-3712 - Bochen Pang, Chaozhuo Li, Yuming Liu, Jianxun Lian, Jianan Zhao, Hao Sun, Weiwei Deng, Xing Xie, Qi Zhang:
Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads. 3713-3721 - Hyoshin Park, Justice Darko, Niharika Deshpande, Venktesh Pandey, Hui Su, Masahiro Ono, Dedrick Barkely, Larkin Folsom, Derek J. Posselt, Steve A. Chien:
Temporal Multimodal Multivariate Learning. 3722-3732 - Sungwon Park, Karandeep Singh, Arjun Nellikkattil, Elke Zeller, Tung-Duong Mai, Meeyoung Cha:
Downscaling Earth System Models with Deep Learning. 3733-3742 - Birgit Pfitzmann, Christoph Auer, Michele Dolfi, Ahmed S. Nassar, Peter W. J. Staar:
DocLayNet: A Large Human-Annotated Dataset for Document-Layout Segmentation. 3743-3751 - Prakruthi Prabhakar, Yiping Yuan, Guangyu Yang, Wensheng Sun, Ajith Muralidharan:
Multi-objective Optimization of Notifications Using Offline Reinforcement Learning. 3752-3760 - Hangwei Qian, Tian Tian, Chunyan Miao:
What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks? 3761-3771 - Xufeng Qian, Yue Xu, Fuyu Lv, Shengyu Zhang, Ziwen Jiang, Qingwen Liu, Xiaoyi Zeng, Tat-Seng Chua, Fei Wu:
Intelligent Request Strategy Design in Recommender System. 3772-3782 - Kevin Quinn, Evimaria Terzi, Mark Crovella:
Characterizing Covid Waves via Spatio-Temporal Decomposition. 3783-3791 - Kaushik Rangadurai, Yiqun Liu, Siddarth Malreddy, Xiaoyi Liu, Piyush Maheshwari, Vishwanath Sangale, Fedor Borisyuk:
NxtPost: User To Post Recommendations In Facebook Groups. 3792-3800 - Nathalie Rauschmayr, Sami Kama, Muhyun Kim, Miyoung Choi, Krishnaram Kenthapadi:
Profiling Deep Learning Workloads at Scale using Amazon SageMaker. 3801-3809 - Houxing Ren, Jingyuan Wang, Wayne Xin Zhao:
Generative Adversarial Networks Enhanced Pre-training for Insufficient Electronic Health Records Modeling. 3810-3818 - Benedek Rozemberczki, Charles Tapley Hoyt, Anna Gogleva, Piotr Grabowski, Klas Karis, Andrej Lamov, Andriy Nikolov, Sebastian Nilsson, Michaël Ughetto, Yu Wang, Tyler Derr, Benjamin M. Gyori:
ChemicalX: A Deep Learning Library for Drug Pair Scoring. 3819-3828 - Sijie Ruan, Cheng Long, Zhipeng Ma, Jie Bao, Tianfu He, Ruiyuan Li, Yiheng Chen, Shengnan Wu, Yu Zheng:
Service Time Prediction for Delivery Tasks via Spatial Meta-Learning. 3829-3837 - Soheil Sadeghi Eshkevari, Xiaocheng Tang, Zhiwei Qin, Jinhan Mei, Cheng Zhang, Qianying Meng, Jia Xu:
Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplace. 3838-3848 - Rajdeep Sarkar, Sourav Dutta, Haytham Assem, Mihael Arcan, John P. McCrae:
Semantic Aware Answer Sentence Selection Using Self-Learning Based Domain Adaptation. 3849-3857 - Yu Sha, Shuiping Gou, Johannes Faber, Bo Liu, Wei Li, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou:
Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space. 3858-3868 - Jun Shi, Chengming Jiang, Aman Gupta, Mingzhou Zhou, Yunbo Ouyang, Qiang Charles Xiao, Qingquan Song, Yi (Alice) Wu, Haichao Wei, Huiji Gao:
Generalized Deep Mixed Models. 3869-3877 - Jongkyung Shin, Changhun Lee, Chiehyeon Lim, Yunmo Shin, Junseok Lim:
Recommendation in Offline Stores: A Gamification Approach for Learning the Spatiotemporal Representation of Indoor Shopping. 3878-3888 - M. Ashraf Siddiquee, Vinícius M. A. de Souza, Glenn Eli Baker, Abdullah Mueen:
Septor: Seismic Depth Estimation Using Hierarchical Neural Networks. 3889-3897 - Ian Simpson, Ryan J. Beal, Duncan Locke, Timothy J. Norman:
Seq2Event: Learning the Language of Soccer Using Transformer-based Match Event Prediction. 3898-3908 - Xiran Song, Jianxun Lian, Hong Huang, Mingqi Wu, Hai Jin, Xing Xie:
Friend Recommendations with Self-Rescaling Graph Neural Networks. 3909-3919 - Aseem Srivastava, Tharun Suresh, Sarah Peregrine Lord, Md. Shad Akhtar, Tanmoy Chakraborty:
Counseling Summarization Using Mental Health Knowledge Guided Utterance Filtering. 3920-3930 - Giorgos Stoilos, Nikos Papasarantopoulos, Pavlos Vougiouklis, Patrik Bansky:
Type Linking for Query Understanding and Semantic Search. 3931-3940 - Yueyang Su, Di Yao, Xiaokai Chu, Wenbin Li, Jingping Bi, Shiwei Zhao, Runze Wu, Shize Zhang, Jianrong Tao, Hao Deng:
Few-shot Learning for Trajectory-based Mobile Game Cheating Detection. 3941-3949 - Jiahui Sun, Haiming Jin, Zhaoxing Yang, Lu Su, Xinbing Wang:
Optimizing Long-Term Efficiency and Fairness in Ride-Hailing via Joint Order Dispatching and Driver Repositioning. 3950-3960 - Rukma Talwadker, Surajit Chakrabarty, Aditya Pareek, Tridib Mukherjee, Deepak Saini:
CognitionNet: A Collaborative Neural Network for Play Style Discovery in Online Skill Gaming Platform. 3961-3969 - Yanchao Tan, Chengjun Kong, Leisheng Yu, Pan Li, Chaochao Chen, Xiaolin Zheng, Vicki Hertzberg, Carl Yang:
4SDrug: Symptom-based Set-to-set Small and Safe Drug Recommendation. 3970-3980 - Ha Xuan Tran, Thuc Duy Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao, Tony Waters:
What is the Most Effective Intervention to Increase Job Retention for this Disabled Worker? 3981-3991 - Leonie von Wahl, Nicolas Tempelmeier, Ashutosh Sao, Elena Demidova:
Reinforcement Learning-based Placement of Charging Stations in Urban Road Networks. 3992-4000 - Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou:
A Graph Learning Based Framework for Billion-Scale Offline User Identification. 4001-4009 - Dong Wang, Shaoguang Yan, Yunqing Xia, Kavé Salamatian, Weiwei Deng, Qi Zhang:
Learning Supplementary NLP Features for CTR Prediction in Sponsored Search. 4010-4020 - Haozhe Wang, Chao Du, Panyan Fang, Shuo Yuan, Xuming He, Liang Wang, Bo Zheng:
ROI-Constrained Bidding via Curriculum-Guided Bayesian Reinforcement Learning. 4021-4031 - Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang:
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365. 4032-4040 - Mudan Wang, Huan Yan, Hongjie Sui, Fan Zuo, Yue Liu, Yong Li:
Learning to Discover Causes of Traffic Congestion with Limited Labeled Data. 4041-4049 - Shuai Wang, Junke Lu, Baoshen Guo, Zheng Dong:
RT-VeD: Real-Time VoI Detection on Edge Nodes with an Adaptive Model Selection Framework. 4050-4058 - Tingting Wang, Shixun Huang, Zhifeng Bao, J. Shane Culpepper, Reza Arablouei:
Representative Routes Discovery from Massive Trajectories. 4059-4069 - Xiao-Yu Wang, Bin Tan, Yonghui Guo, Tao Yang, Dongbo Huang, Lan Xu, Nikolaos M. Freris, Hao Zhou, Xiangyang Li:
CONFLUX: A Request-level Fusion Framework for Impression Allocation via Cascade Distillation. 4070-4078 - Yansheng Wang, Yongxin Tong, Zimu Zhou, Ziyao Ren, Yi Xu, Guobin Wu, Weifeng Lv:
Fed-LTD: Towards Cross-Platform Ride Hailing via Federated Learning to Dispatch. 4079-4089 - Yichao Wang, Huifeng Guo, Bo Chen, Weiwen Liu, Zhirong Liu, Qi Zhang, Zhicheng He, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation. 4090-4099 - Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed H. Chi, Minmin Chen:
Surrogate for Long-Term User Experience in Recommender Systems. 4100-4109 - Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. 4110-4120 - Zhiyuan Wang, Fan Zhou, Wenxuan Zeng, Goce Trajcevski, Chunjing Xiao, Yong Wang, Kai Chen:
Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks. 4121-4131 - Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana:
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values. 4132-4142 - Haomin Wen, Youfang Lin, Xiaowei Mao, Fan Wu, Yiji Zhao, Haochen Wang, Jianbin Zheng, Lixia Wu, Haoyuan Hu, Huaiyu Wan:
Graph2Route: A Dynamic Spatial-Temporal Graph Neural Network for Pick-up and Delivery Route Prediction. 4143-4152 - Hongzhi Wen, Jiayuan Ding, Wei Jin, Yiqi Wang, Yuying Xie, Jiliang Tang:
Graph Neural Networks for Multimodal Single-Cell Data Integration. 4153-4163 - Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang, Xing Xie:
FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling. 4164-4172 - Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel R. Jiang, Eytan Bakshy:
Interpretable Personalized Experimentation. 4173-4183 - Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosic, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec:
Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator. 4184-4194 - Zhuolin Wu, Li Wang, Fangsheng Huang, Linjun Zhou, Yu Song, Chengpeng Ye, Pengyu Nie, Hao Ren, Jinghua Hao, Renqing He, Zhizhao Sun:
A Framework for Multi-stage Bonus Allocation in Meal Delivery Platform. 4195-4203 - Ding Xiang, Rebecca West, Jiaqi Wang, Xiquan Cui, Jinzhou Huang:
Multi Armed Bandit vs. A/B Tests in E-commence - Confidence Interval and Hypothesis Test Power Perspectives. 4204-4214 - Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Bhuvan Middha, Fangzhao Wu, Xing Xie:
Training Large-Scale News Recommenders with Pretrained Language Models in the Loop. 4215-4225 - Ruobing Xie, Qi Liu, Liangdong Wang, Shukai Liu, Bo Zhang, Leyu Lin:
Contrastive Cross-domain Recommendation in Matching. 4226-4236 - Jia Xu, Fei Xiong, Zulong Chen, Mingyuan Tao, Liangyue Li, Quan Lu:
G2NET: A General Geography-Aware Representation Network for Hotel Search Ranking. 4237-4247 - Sheng Xu, Xiaojun Wan, Sen Hu, Mengdi Zhou, Teng Xu, Hongbin Wang, Haitao Mi:
COSSUM: Towards Conversation-Oriented Structured Summarization for Automatic Medical Insurance Assessment. 4248-4256 - Zhenhui Xu, Meng Zhao, Liqun Liu, Lei Xiao, Xiaopeng Zhang, Bifeng Zhang:
Mixture of Virtual-Kernel Experts for Multi-Objective User Profile Modeling. 4257-4267 - Bing Xue, York Jiao, Thomas George Kannampallil, Bradley A. Fritz, Christopher Ryan King, Joanna Abraham, Michael Avidan, Chenyang Lu:
Perioperative Predictions with Interpretable Latent Representation. 4268-4278 - Jiawei Xue, Takahiro Yabe, Kota Tsubouchi, Jianzhu Ma, Satish V. Ukkusuri:
Multiwave COVID-19 Prediction from Social Awareness Using Web Search and Mobility Data. 4279-4289 - Siqiao Xue, Chao Qu, Xiaoming Shi, Cong Liao, Shiyi Zhu, Xiaoyu Tan, Lintao Ma, Shiyu Wang, Shijun Wang, Yun Hu, Lei Lei, Yangfei Zheng, Jianguo Li, James Zhang:
A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud. 4290-4299 - Le Yan, Zhen Qin, Xuanhui Wang, Michael Bendersky, Marc Najork:
Scale Calibration of Deep Ranking Models. 4300-4309 - Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang:
CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis. 4310-4320 - Jianzhong Yang, Xiaoqing Ye, Bin Wu, Yanlei Gu, Ziyu Wang, Deguo Xia, Jizhou Huang:
DuARE: Automatic Road Extraction with Aerial Images and Trajectory Data at Baidu Maps. 4321-4331 - Jiuding Yang, Weidong Guo, Bang Liu, Yakun Yu, Chaoyue Wang, Jinwen Luo, Linglong Kong, Di Niu, Zhen Wen:
TAG: Toward Accurate Social Media Content Tagging with a Concept Graph. 4332-4341 - Di Yao, Chang Gong, Lei Zhang, Sheng Chen, Jingping Bi:
CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attribution. 4342-4352 - Jiangchao Yao, Feng Wang, Xichen Ding, Shaohu Chen, Bo Han, Jingren Zhou, Hongxia Yang:
Device-cloud Collaborative Recommendation via Meta Controller. 4353-4362 - Shaowei Yao, Jiwei Tan, Xi Chen, Juhao Zhang, Xiaoyi Zeng, Keping Yang:
ReprBERT: Distilling BERT to an Efficient Representation-Based Relevance Model for E-Commerce. 4363-4371 - Eric Ye, Xiao Bai, Neil O'Hare, Eliyar Asgarieh, Kapil Thadani, Francisco Perez-Sorrosal, Sujyothi Adiga:
Multilingual Taxonomic Web Page Classification for Contextual Targeting at Yahoo. 4372-4380 - Junyao Ye, Jingyong Su, Yilong Cao:
A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling. 4381-4390 - Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng, Huiyuan Chen, Javid Ebrahimi, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang:
Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph. 4391-4401 - Changchang Yin, Sayoko E. Moroi, Ping Zhang:
Predicting Age-Related Macular Degeneration Progression with Contrastive Attention and Time-Aware LSTM. 4402-4412 - Fudan Yu, Wenxuan Ao, Huan Yan, Guozhen Zhang, Wei Wu, Yong Li:
Spatio-Temporal Vehicle Trajectory Recovery on Road Network Based on Traffic Camera Video Data. 4413-4421 - Jifan Yu, Xiaohan Zhang, Yifan Xu, Xuanyu Lei, Xinyu Guan, Jing Zhang, Lei Hou, Juanzi Li, Jie Tang:
XDAI: A Tuning-free Framework for Exploiting Pre-trained Language Models in Knowledge Grounded Dialogue Generation. 4422-4432 - Licheng Yu, Jun Chen, Animesh Sinha, Mengjiao Wang, Yu Chen, Tamara L. Berg, Ning Zhang:
CommerceMM: Large-Scale Commerce MultiModal Representation Learning with Omni Retrieval. 4433-4442 - Tan Yu, Jie Liu, Yi Yang, Yi Li, Hongliang Fei, Ping Li:
EGM: Enhanced Graph-based Model for Large-scale Video Advertisement Search. 4443-4451 - Han Yue, Steve Q. Xia, Hongfu Liu:
Multi-task Envisioning Transformer-based Autoencoder for Corporate Credit Rating Migration Early Prediction. 4452-4460 - Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu:
AutoShard: Automated Embedding Table Sharding for Recommender Systems. 4461-4471 - Ruohan Zhan, Changhua Pei, Qiang Su, Jianfeng Wen, Xueliang Wang, Guanyu Mu, Dong Zheng, Peng Jiang, Kun Gai:
Deconfounding Duration Bias in Watch-time Prediction for Video Recommendation. 4472-4481 - Chongsheng Zhang, Bin Wang, Ke Chen, Ruixing Zong, Bofeng Mo, Yi Men, George Almpanidis, Shanxiong Chen, Xiangliang Zhang:
Data-Driven Oracle Bone Rejoining: A Dataset and Practical Self-Supervised Learning Scheme. 4482-4492 - Jianjin Zhang, Zheng Liu, Weihao Han, Shitao Xiao, Ruicheng Zheng, Yingxia Shao, Hao Sun, Hanqing Zhu, Premkumar Srinivasan, Weiwei Deng, Qi Zhang, Xing Xie:
Uni-Retriever: Towards Learning the Unified Embedding Based Retriever in Bing Sponsored Search. 4493-4501 - Qi Zhang, Tiancheng Wu, Peichen Zhou, Shan Zhou, Yuan Yang, Xiulang Jin:
Felicitas: Federated Learning in Distributed Cross Device Collaborative Frameworks. 4502-4509 - Qihua Zhang, Junning Liu, Yuzhuo Dai, Yiyan Qi, Yifan Yuan, Kunlun Zheng, Fan Huang, Xianfeng Tan:
Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systems. 4510-4520 - Rongzhi Zhang, Rebecca West, Xiquan Cui, Chao Zhang:
Adaptive Multi-view Rule Discovery for Weakly-Supervised Compatible Products Prediction. 4521-4529 - Sean Zhang, Varun Ursekar, Leman Akoglu:
Sparx: Distributed Outlier Detection at Scale. 4530-4540 - Shengming Zhang, Yanchi Liu, Xuchao Zhang, Wei Cheng, Haifeng Chen, Hui Xiong:
CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event Sequences. 4541-4550 - Shiwei Zhang, Jichao Sun, Yu Huang, Xueqi Ding, Yefeng Zheng:
Medical Symptom Detection in Intelligent Pre-Consultation Using Bi-directional Hard-Negative Noise Contrastive Estimation. 4551-4559 - Wentao Zhang, Ziqi Yin, Zeang Sheng, Yang Li, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui:
Graph Attention Multi-Layer Perceptron. 4560-4570 - Wayne Xin Zhao, Kun Zhou, Zheng Gong, Beichen Zhang, Yuanhang Zhou, Jing Sha, Zhigang Chen, Shijin Wang, Cong Liu, Ji-Rong Wen:
JiuZhang: A Chinese Pre-trained Language Model for Mathematical Problem Understanding. 4571-4581 - Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis:
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs. 4582-4591 - Zhi Zheng, Zhaopeng Qiu, Hui Xiong, Xian Wu, Tong Xu, Enhong Chen, Xiangyu Zhao:
DDR: Dialogue Based Doctor Recommendation for Online Medical Service. 4592-4600 - Johan Kok Zhi Kang, Suwei Yang, Suriya Venkatesan, Sien Yi Tan, Feng Cheng, Bingsheng He:
Dynamic Graph Segmentation for Deep Graph Neural Networks. 4601-4611 - Kailiang Zhong, Fengtong Xiao, Yan Ren, Yaorong Liang, Wenqing Yao, Xiaofeng Yang, Ling Cen:
DESCN: Deep Entire Space Cross Networks for Individual Treatment Effect Estimation. 4612-4620 - Chenxu Zhu, Peng Du, Weinan Zhang, Yong Yu, Yang Cao:
Combo-Fashion: Fashion Clothes Matching CTR Prediction with Item History. 4621-4629 - Chenxu Zhu, Peng Du, Xianghui Zhu, Weinan Zhang, Yong Yu, Yang Cao:
User-tag Profile Modeling in Recommendation System via Contrast Weighted Tag Masking. 4630-4638 - Dingyi Zhuang, Shenhao Wang, Haris N. Koutsopoulos, Jinhua Zhao:
Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks. 4639-4647 - Zefang Zong, Hansen Wang, Jingwei Wang, Meng Zheng, Yong Li:
RBG: Hierarchically Solving Large-Scale Routing Problems in Logistic Systems via Reinforcement Learning. 4648-4658
Health Day Papers
- Jiangzhuo Chen, Stefan Hoops, Achla Marathe, Henning S. Mortveit, Bryan L. Lewis, Srinivasan Venkatramanan, Arash Haddadan, Parantapa Bhattacharya, Abhijin Adiga, Anil Vullikanti, Aravind Srinivasan, Mandy L. Wilson, Gal Ehrlich, Maier Fenster, Stephen G. Eubank, Christopher L. Barrett, Madhav V. Marathe:
Effective Social Network-Based Allocation of COVID-19 Vaccines. 4675-4683 - Qianyue Hao, Wenzhen Huang, Fengli Xu, Kun Tang, Yong Li:
Reinforcement Learning Enhances the Experts: Large-scale COVID-19 Vaccine Allocation with Multi-factor Contact Network. 4684-4694 - Weijie He, Ting Chen:
Scalable Online Disease Diagnosis via Multi-Model-Fused Actor-Critic Reinforcement Learning. 4695-4703 - Babaniyi Yusuf Olaniyi, Ana Fernández del Río, África Periáñez, Lauren Bellhouse:
User Engagement in Mobile Health Applications. 4704-4712 - Ziyang Song, Yuanyi Hu, Aman Verma, David L. Buckeridge, Yue Li:
Automatic Phenotyping by a Seed-guided Topic Model. 4713-4723 - Mengying Sun, Jing Xing, Han Meng, Huijun Wang, Bin Chen, Jiayu Zhou:
MolSearch: Search-based Multi-objective Molecular Generation and Property Optimization. 4724-4732 - Carl Yang, Hongwen Song, Mingyue Tang, Leon Danon, Ymir Vigfusson:
Dynamic Network Anomaly Modeling of Cell-Phone Call Detail Records for Infectious Disease Surveillance. 4733-4742 - Yi Yang, Yanqiao Zhu, Hejie Cui, Xuan Kan, Lifang He, Ying Guo, Carl Yang:
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning. 4743-4751 - Yuan Yuan, Jingtao Ding, Huandong Wang, Depeng Jin, Yong Li:
Activity Trajectory Generation via Modeling Spatiotemporal Dynamics. 4752-4762 - Yu Zhao, Yunxin Li, Yuxiang Wu, Baotian Hu, Qingcai Chen, Xiaolong Wang, Yuxin Ding, Min Zhang:
Medical Dialogue Response Generation with Pivotal Information Recalling. 4763-4771
Tutorial Overviews
- Imad Aouali, Amine Benhalloum, Martin Bompaire, Achraf Ait Sidi Hammou, Sergey Ivanov, Benjamin Heymann, David Rohde, Otmane Sakhi, Flavian Vasile, Maxime Vono:
Reward Optimizing Recommendation using Deep Learning and Fast Maximum Inner Product Search. 4772-4773 - Longbing Cao, Philip S. Yu, Zhilin Zhao:
Shallow and Deep Non-IID Learning on Complex Data. 4774-4775 - Rich Caruana, Harsha Nori:
Why Data Scientists Prefer Glassbox Machine Learning: Algorithms, Differential Privacy, Editing and Bias Mitigation. 4776-4777 - Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy:
Hyperbolic Neural Networks: Theory, Architectures and Applications. 4778-4779 - Watson W. K. Chua, Lu Li, Alvina Goh:
Classifying Multimodal Data Using Transformers. 4780-4781 - Kaize Ding, Chuxu Zhang, Jie Tang, Nitesh V. Chawla, Huan Liu:
Toward Graph Minimally-Supervised Learning. 4782-4783 - Ahmed El-Kishky, Michael M. Bronstein, Ying Xiao, Aria Haghighi:
Graph-based Representation Learning for Web-scale Recommender Systems. 4784-4785 - Nick Erickson, Xingjian Shi, James Sharpnack, Alexander J. Smola:
Multimodal AutoML for Image, Text and Tabular Data. 4786-4787 - Parker Erickson, Victor E. Lee, Feng Shi, Jiliang Tang:
Efficient Machine Learning on Large-Scale Graphs. 4788-4789 - Yi R. Fung, Kung-Hsiang Huang, Preslav Nakov, Heng Ji:
The Battlefront of Combating Misinformation and Coping with Media Bias. 4790-4791 - Rajeev Gupta, Ranganath Kondapally:
Large-Scale Information Extraction under Privacy-Aware Constraints. 4792-4793 - Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar, Jason Tsay:
Gradual AutoML using Lale. 4794-4795 - Shuiwang Ji, Meng Liu, Yi Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Zhao Xu, Haiyang Yu:
Frontiers of Graph Neural Networks with DIG. 4796-4797 - Jian Kang, Hanghang Tong:
Algorithmic Fairness on Graphs: Methods and Trends. 4798-4799 - Krishnaram Kenthapadi, Himabindu Lakkaraju, Pradeep Natarajan, Mehrnoosh Sameki:
Model Monitoring in Practice: Lessons Learned and Open Challenges. 4800-4801 - Yaliang Li, Bolin Ding, Jingren Zhou:
A Practical Introduction to Federated Learning. 4802-4803 - Manish Marwah, Martin F. Arlitt:
Deep Learning for Network Traffic Data. 4804-4805 - Yu Meng, Jiaxin Huang, Yu Zhang, Jiawei Han:
Adapting Pretrained Representations for Text Mining. 4806-4807 - Jacob Montiel, Hoang-Anh Ngo, Minh-Huong Le Nguyen, Albert Bifet:
Online Clustering: Algorithms, Evaluation, Metrics, Applications and Benchmarking. 4808-4809 - Linsey Pang, Wei Liu, Keng-hao Chang, Xue Li, Moumita Bhattacharya, Xianjing Liu, Stephen Guo:
Deep Search Relevance Ranking in Practice. 4810-4811 - Dhaval Patel, Dzung Phan, Markus Mueller, Amaresh Rajasekharan:
Toolkit for Time Series Anomaly Detection. 4812-4813 - Hima Patel, Shanmukha C. Guttula, Ruhi Sharma Mittal, Naresh Manwani, Laure Berti-Équille, Abhijit Manatkar:
Advances in Exploratory Data Analysis, Visualisation and Quality for Data Centric AI Systems. 4814-4815 - Sara Rabhi, Ronay Ak, Marc Romeijn, Gabriel de Souza Pereira Moreira, Benedikt D. Schifferer:
Reducing the Friction for Building Recommender Systems with Merlin. 4816-4817 - Nitendra Rajput, Karamjit Singh:
Temporal Graph Learning for Financial World: Algorithms, Scalability, Explainability & Fairness. 4818-4819 - Brad Rees, Xiaoyun Wang, Joe Eaton, Onur Yilmaz, Rick Ratzel, Dominique LaSalle:
Accelerated GNN Training with DGL and RAPIDS cuGraph in a Fraud Detection Workflow. 4820-4821 - Alexander Rodríguez, Harshavardhan Kamarthi, B. Aditya Prakash:
Epidemic Forecasting with a Data-Centric Lens. 4822-4823 - Yuta Saito, Thorsten Joachims:
Counterfactual Evaluation and Learning for Interactive Systems: Foundations, Implementations, and Recent Advances. 4824-4825 - Omprakash Sonie, Abir Chakraborty, Ankan Mullick:
concept2code: Deep Reinforcement Learning for Conversational AI. 4826-4827 - Chi Wang, Qingyun Wu, Xueqing Liu, Luis Quintanilla:
Automated Machine Learning & Tuning with FLAML. 4828-4829 - Wentao Wang, Han Xu, Yuxuan Wan, Jie Ren, Jiliang Tang:
Towards Adversarial Learning: From Evasion Attacks to Poisoning Attacks. 4830-4831 - Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han:
New Frontiers of Scientific Text Mining: Tasks, Data, and Tools. 4832-4833 - Zichen Wang, Vassilis N. Ioannidis, Huzefa Rangwala, Tatsuya Arai, Ryan Brand, Mufei Li, Yohei Nakayama:
Graph Neural Networks in Life Sciences: Opportunities and Solutions. 4834-4835 - Qingsong Wen, Linxiao Yang, Tian Zhou, Liang Sun:
Robust Time Series Analysis and Applications: An Industrial Perspective. 4836-4837 - Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang:
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. 4838-4839 - Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo:
Graph Neural Networks: Foundation, Frontiers and Applications. 4840-4841 - Da Xu, Chuanwei Ruan:
Modern Theoretical Tools for Designing Information Retrieval System. 4842-4843 - Guang Yang, Ninad Kulkarni, Paavani Dua, Dipika Khullar, Alex Anto Chirayath:
Anomaly Detection for Spatiotemporal Data in Action. 4844-4845 - Sophia Yang, Marc Skov Madsen, James A. Bednar:
HoloViz: Visualization and Interactive Dashboards in Python. 4846-4847 - Hsiang-Fu Yu, Jiong Zhang, Wei-Cheng Chang, Jyun-Yu Jiang, Wei Li, Cho-Jui Hsieh:
PECOS: Prediction for Enormous and Correlated Output Spaces. 4848-4849
Workshop Summaries
- Bijaya Adhikari, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Sarah Kefayati, Alexander Rodríguez, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash:
epiDAMIK 5.0: The 5th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. 4850-4851 - Abraham Bagherjeiran, Nemanja Djuric, Mihajlo Grbovic, Kuang-Chih Lee, Kun Liu, Wei Liu, Linsey Pang, Vladan Radosavljevic, Suju Rajan, Kexin Xie:
AdKDD 2022. 4852-4853 - Pamela Bhattacharya, Jing Gao, Meng Jiang, Mehran Kafai, Srijan Kumar, Qi Li, Neil Shah, Sihong Xie, Philip S. Yu, Ming Zeng:
Joint International Workshop on Misinformation and Misbehavior Mining on the Web & Making a Credible Web for Tomorrow (MIS2-TrueFact). 4854-4855 - Yi Bu, Meijun Liu, Yujia Zhai, Ying Ding, Feng Xia, Daniel E. Acuña, Yi Zhang:
International Workshop on Data-driven Science of Science. 4856-4857 - Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu:
The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022). 4858-4859 - Roberto Corizzo, Junfeng Ge, Colin Bellinger, Xiaoqiang Zhu, Paula Branco, Kuang-chih Lee, Nathalie Japkowicz, Ruiming Tang, Tao Zhuang, Han Zhu, Biye Jiang, Jiaxin Mao, Weinan Zhang:
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. 4860-4861 - Xiquan Cui, Vachik S. Dave, Yi Su, Khalifeh Al Jadda, Srijan Kumar, Julian J. McAuley, Tao Ye, Kamelia Aryafar, Mohammed Korayem:
2nd Workshop on Online and Adaptive Recommender Systems (OARS). 4862-4863 - Ying Ding, Amit P. Sheth, Krzysztof W. Janowicz, Sergio Baranzini, Sharat Israni, Ilkay Altintas, Lilit Yeghiazarian, Ellie Young, Sam Klein:
International Workshop on Knowledge Graphs: Open Knowledge Network. 4864-4865 - Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan, Rose Yu:
Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice. 4866-4867 - Shobeir Fakhraei, Tim Weninger, Neil Shah, Sami Abu-El-Haija, Saurabh Verma, Tara Safavi:
17th International Workshop on Mining and Learning with Graphs (MLG). 4868-4869 - Usama M. Fayyad, Hamit Hamutcu:
3rd IADSS Workshop on Data Science Standards - Hiring, Assessing and Upskilling Data Science Talent. 4870-4871 - Snehalkumar (Neil) S. Gaikwad, Shankar Iyer, Dalton D. Lunga, Takahiro Yabe, Xiaofan Liang, Bhavani Ananthabhotla, Nikhil Behari, Sreelekha Guggilam, Guanghua Chi:
Data-driven Humanitarian Mapping and Policymaking: Toward Planetary-Scale Resilience, Equity, and Sustainability. 4872-4873 - Dmitri Goldenberg, Elena Sokolova, Shir Meir Lador, Amit Mandelbaum, Irina Vasilinetc, Ankit Jain:
Workshop on Applied Machine Learning Management. 4874-4875 - Neha Gupta, Zhenyu Zhao, Mert Bay, Anbang Xu, Faisal Farooq:
1st Workshop on End-End Customer Journey Optimization. 4876-4877 - Zhe Jiang, Liang Zhao, Xun Zhou, Robert N. Stewart, Junbo Zhang, Shashi Shekhar, Jieping Ye:
DeepSpatial'22: The 3rd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems. 4878-4879 - Patrick Koch, Brett Wujek, Jun Liu, Jun Huan, Tao Wang:
The Sixth International Workshop on Automation in Machine Learning. 4880-4881 - Senthil Kumar, Leman Akoglu, Nitesh V. Chawla, Saurabh Nagrecha, Vidyut M. Naware, Tanveer A. Faruquie, Hays McCormick:
KDD Workshop on Machine Learning in Finance. 4882-4883 - Thuc Duy Le, Lin Liu, Emre Kiciman, Sofia Triantafyllou, Huan Liu:
The KDD 2022 Workshop on Causal Discovery (CD2022). 4884-4885 - Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 11th International Workshop on Urban Computing. 4886-4887 - Sumit Negi, Manisha Verma, Rajdeep H. Banerjee, Pooja A, Lydia B. Chilton, Mithun Das Gupta, Vinay P. Namboodiri, Dinesh Garg:
First Workshop on Content Understanding and Generation for E-commerce. 4888-4889 - Ani Nenkova, Douglas Burdick, Benjamin Han, Dave Lewis, Sandeep Tata, Dan Tecuci:
DI-2022: The Third Document Intelligence Workshop. 4890-4891 - Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich:
ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation. 4892-4893 - Claudia Plant, Nina C. Hubig, Junming Shao, Alvitta Ottley, Liang Gou, Torsten Möller, Adam Perer, Alexander Lex, Anamaria Crisan:
Visualization in Data Science VDS @ KDD 2022. 4894-4895 - Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka:
8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. 4896-4897 - Zhiwei (Tony) Qin, Liangjie Hong, Rui Song, Hongtu Zhu, Mohammed Korayem, Haiyan Luo, Michael I. Jordan:
Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond. 4898-4899 - Sagar Samtani, Gang Wang, Ali Ahmadzadeh, Arridhana Ciptadi, Shanchieh Yang, Hsinchun Chen:
ACM KDD AI4Cyber/MLHat: Workshop on AI-enabled Cybersecurity Analytics and Deployable Defense. 4900-4901 - Avadhut Sardeshmukh, Sreedhar Reddy, Gautham B. P., Ankit Agrawal:
Machine Learning for Materials Science (MLMS). 4902-4903 - Shoujin Wang, Ninghao Liu, Xiuzhen Zhang, Yan Wang, Francesco Ricci, Bamshad Mobasher:
Data Science and Artificial Intelligence for Responsible Recommendations. 4904-4905 - Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2022). 4906-4907 - Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner:
Workshop on Applied Data Science for Healthcare (DSHealth): Transparent and Human-centered AI. 4908-4909 - Da Yan, Catia Pesquita, Carsten Görg, Jake Y. Chen, Mohammed J. Zaki:
21th International Workshop on Data Mining in Bioinformatics (BIOKDD 2022). 4910-4911 - Jian Zhang, Jian Tang, Yiran Chen, Jie Liu, Jieping Ye, Marilyn Wolf, Vijaykrishnan Narayanan, Mani B. Srivastava, Michael I. Jordan, Victor Bahl:
The 5th Artificial Intelligence of Things (AIoT) Workshop. 4912-4913 - Chen Zhao, Feng Chen, Xintao Wu, Christopher Funk, Anthony Hoogs:
1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22). 4914-4915
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