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2020 – today
- 2024
- [j55]Kaili Ma, Han Yang
, Shanchao Yang, Kangfei Zhao, Lanqing Li
Solving the non-submodular network collapse problems via Decision Transformer. Neural Networks 176: 106328 (2024) - [j54]Chenguang Zheng
GE2: A General and Efficient Knowledge Graph Embedding Learning System. Proc. ACM Manag. Data 2(3): 183 (2024) - [j53]Qihui Zhou
Atom: An Efficient Query Serving System for Embedding-based Knowledge Graph Reasoning with Operator-level Batching. Proc. ACM Manag. Data 2(4): 193:1-193:29 (2024) - [j52]Kaihao Ma
PPS: Fair and efficient black-box scheduling for multi-tenant GPU clusters. Parallel Comput. 120: 103082 (2024) - [c107]Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng:
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. AAAI 2024: 16040-16048 - [c106]Guanxian Jiang, Yunjian Zhao, Yichao Li, Zhi Liu, Tatiana Jin, Wanying Zheng, Boyang Li, James Cheng:
Wings: Efficient Online Multiple Graph Pattern Matching. ICDE 2024: 3013-3027 - [c105]Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng:
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR 2024 - [c104]Yongqiang Chen, Yatao Bian, Bo Han, James Cheng:
How Interpretable Are Interpretable Graph Neural Networks? ICML 2024 - [c103]Da Yan
Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods. KDD 2024: 6627-6632 - [c102]Xinzhe Wang
Detecting and Understanding Self-Deleting JavaScript Code. WWW 2024: 1768-1778 - [i66]Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng:
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. CoRR abs/2401.08464 (2024) - [i65]Binghui Xie, Yatao Bian
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR abs/2402.03139 (2024) - [i64]Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang:
Discovery of the Hidden World with Large Language Models. CoRR abs/2402.03941 (2024) - [i63]Yongqiang Chen, Yatao Bian
How Interpretable Are Interpretable Graph Neural Networks? CoRR abs/2406.07955 (2024) - [i62]Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian:
HIGHT: Hierarchical Graph Tokenization for Graph-Language Alignment. CoRR abs/2406.14021 (2024) - 2023
- [j51]Tatiana Jin
Circinus: Fast Redundancy-Reduced Subgraph Matching. Proc. ACM Manag. Data 1(1): 12:1-12:26 (2023) - [j50]Kaihao Ma
FEC: Efficient Deep Recommendation Model Training with Flexible Embedding Communication. Proc. ACM Manag. Data 1(2): 165:1-165:21 (2023) - [j49]Barakeel Fanseu Kamhoua
GRACE: A General Graph Convolution Framework for Attributed Graph Clustering. ACM Trans. Knowl. Discov. Data 17(3): 31:1-31:31 (2023) - [j48]Kaili Ma, Garry Yang, Han Yang, Yongqiang Chen, James Cheng:
Calibrating and Improving Graph Contrastive Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c101]James Cheng
Graph Feature Management: Impact, Challenges and Opportunities. GRADES-NDA@SIGMOD 2023: 2:1 - [c100]Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng:
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR 2023 - [c99]Peiqi Yin
DGI: An Easy and Efficient Framework for GNN Model Evaluation. KDD 2023: 5439-5450 - [c98]Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng:
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NeurIPS 2023 - [c97]Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng:
Understanding and Improving Feature Learning for Out-of-Distribution Generalization. NeurIPS 2023 - [c96]Zhenkun Cai, Qihui Zhou, Xiao Yan, Da Zheng, Xiang Song, Chenguang Zheng, James Cheng, George Karypis:
DSP: Efficient GNN Training with Multiple GPUs. PPoPP 2023: 392-404 - [i61]Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian
Towards Understanding Feature Learning in Out-of-Distribution Generalization. CoRR abs/2304.11327 (2023) - [i60]Zihao Wang, Yongqiang Chen, Yang Duan, Weijiang Li, Bo Han, James Cheng, Hanghang Tong:
Towards out-of-distribution generalizable predictions of chemical kinetics properties. CoRR abs/2310.03152 (2023) - [i59]Yongqiang Chen, Yatao Bian
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? CoRR abs/2310.19035 (2023) - [i58]Yongqiang Chen, Binghui Xie, Kaiwen Zhou, Bo Han, Yatao Bian
Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes. CoRR abs/2311.18194 (2023) - [i57]Yuntao Gui, Xiao Yan, Peiqi Yin, Han Yang, James Cheng:
SPT: Fine-Tuning Transformer-based Language Models Efficiently with Sparsification. CoRR abs/2312.10365 (2023) - 2022
- [j47]Chenguang Zheng
ByteGNN: Efficient Graph Neural Network Training at Large Scale. Proc. VLDB Endow. 15(6): 1228-1242 (2022) - [j46]Hongzhi Chen, Changji Li
G-Tran: A High Performance Distributed Graph Database with a Decentralized Architecture. Proc. VLDB Endow. 15(11): 2545-2558 (2022) - [j45]Changji Li
ByteGraph: A High-Performance Distributed Graph Database in ByteDance. Proc. VLDB Endow. 15(12): 3306-3318 (2022) - [j44]Pengfei Zuo
RACE: One-sided RDMA-conscious Extendible Hashing. ACM Trans. Storage 18(2): 11:1-11:29 (2022) - [j43]Yidi Wu, Kaihao Ma, Xiao Yan
Elastic Deep Learning in Multi-Tenant GPU Clusters. IEEE Trans. Parallel Distributed Syst. 33(1): 144-158 (2022) - [j42]Zhenkun Cai
TensorOpt: Exploring the Tradeoffs in Distributed DNN Training With Auto-Parallelism. IEEE Trans. Parallel Distributed Syst. 33(8): 1967-1981 (2022) - [c95]Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng:
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. AISTATS 2022: 3684-3708 - [c94]Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng:
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. ICLR 2022 - [c93]Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng:
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. ICML 2022: 7144-7163 - [c92]Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng:
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. NeurIPS 2022 - [c91]Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng:
Exact Shape Correspondence via 2D graph convolution. NeurIPS 2022 - [c90]Guanxian Jiang, Qihui Zhou, Tatiana Jin, Boyang Li, Yunjian Zhao, Yichao Li, James Cheng:
VSGM: View-Based GPU-Accelerated Subgraph Matching on Large Graphs. SC 2022: 52:1-52:15 - [c89]Yuntao Gui, Yidi Wu, Han Yang, Tatiana Jin, Boyang Li, Qihui Zhou, James Cheng, Fan Yu:
HGL: Accelerating Heterogeneous GNN Training with Holistic Representation and Optimization. SC 2022: 72:1-72:15 - [i56]Yongqiang Chen, Yonggang Zhang, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng:
Invariance Principle Meets Out-of-Distribution Generalization on Graphs. CoRR abs/2202.05441 (2022) - [i55]Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng:
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. CoRR abs/2202.08057 (2022) - [i54]Binghui Xie, Chenhan Jin, Kaiwen Zhou, James Cheng, Wei Meng:
An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms. CoRR abs/2205.02273 (2022) - [i53]Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng:
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. CoRR abs/2206.07314 (2022) - [i52]Yongqiang Chen
Pareto Invariant Risk Minimization. CoRR abs/2206.07766 (2022) - [i51]Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Ming-Chang Yang:
Efficient Private SCO for Heavy-Tailed Data via Clipping. CoRR abs/2206.13011 (2022) - [i50]Yifan Hou, Jie Zhang, James Cheng, Kaili Ma, Richard T. B. Ma, Hongzhi Chen, Ming-Chang Yang:
Measuring and Improving the Use of Graph Information in Graph Neural Networks. CoRR abs/2206.13170 (2022) - [i49]Yifan Hou, Hongzhi Chen, Changji Li, James Cheng, Ming-Chang Yang:
A Representation Learning Framework for Property Graphs. CoRR abs/2206.13176 (2022) - [i48]Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang:
DGI: Easy and Efficient Inference for GNNs. CoRR abs/2211.15082 (2022) - 2021
- [j41]Guimu Guo
Scalable De Novo Genome Assembly Using a Pregel-Like Graph-Parallel System. IEEE ACM Trans. Comput. Biol. Bioinform. 18(2): 731-744 (2021) - [j40]Yunjian Zhao, Zhi Liu, Yidi Wu, Guanxian Jiang, James Cheng, Kunlong Liu, Xiao Yan:
Timestamped State Sharing for Stream Analytics. IEEE Trans. Parallel Distributed Syst. 32(11): 2691-2704 (2021) - [c88]Han Yang
Rethinking Graph Regularization for Graph Neural Networks. AAAI 2021: 4573-4581 - [c87]Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han:
HyperGraph Convolution Based Attributed HyperGraph Clustering. CIKM 2021: 453-463 - [c86]Zhenkun Cai, Xiao Yan, Yidi Wu, Kaihao Ma, James Cheng, Fan Yu:
DGCL: an efficient communication library for distributed GNN training. EuroSys 2021: 130-144 - [c85]Yidi Wu, Kaihao Ma, Zhenkun Cai, Tatiana Jin, Boyang Li, Chengguang Zheng, James Cheng, Fan Yu:
Seastar: vertex-centric programming for graph neural networks. EuroSys 2021: 359-375 - [c84]Han Yang
Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs. IJCNN 2021: 1-8 - [c83]Yidi Wu, Yuntao Gui
Vertex-Centric Visual Programming for Graph Neural Networks. SIGMOD Conference 2021: 2803-2807 - [c82]Yihui Feng, Zhi Liu, Yunjian Zhao, Tatiana Jin, Yidi Wu, Yang Zhang, James Cheng, Chao Li, Tao Guan:
Scaling Large Production Clusters with Partitioned Synchronization. USENIX ATC 2021: 81-97 - [i47]Kaili Ma
Improving Graph Representation Learning by Contrastive Regularization. CoRR abs/2101.11525 (2021) - [i46]Hongzhi Chen, Changji Li, Chenguang Zheng, Chenghuan Huang, Juncheng Fang, James Cheng, Jie Zhang:
G-Tran: Making Distributed Graph Transactions Fast. CoRR abs/2105.04449 (2021) - [i45]Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng:
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. CoRR abs/2105.12062 (2021) - [i44]Ruize Gao, Feng Liu, Kaiwen Zhou, Gang Niu, Bo Han, James Cheng:
Local Reweighting for Adversarial Training. CoRR abs/2106.15776 (2021) - [i43]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization. CoRR abs/2109.15292 (2021) - 2020
- [j39]James Cheng, Starr Hoffman
Librarians and Administrators on Academic Library Impact Research: Characteristics and Perspectives. Coll. Res. Libr. 81(3) (2020) - [j38]Fanhua Shang
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. 32(1): 188-202 (2020) - [c81]Xinyan Dai, Xiao Yan, Kelvin Kai Wing Ng, Jiu Liu, James Cheng:
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. AAAI 2020: 51-58 - [c80]Jie Liu
Understanding and Improving Proximity Graph Based Maximum Inner Product Search. AAAI 2020: 139-146 - [c79]Yitong Meng, Xinyan Dai, Xiao Yan, James Cheng, Weiwen Liu
PMD: An Optimal Transportation-Based User Distance for Recommender Systems. ECIR (2) 2020: 272-280 - [c78]Tatiana Jin, Zhenkun Cai, Boyang Li, Chengguang Zheng, Guanxian Jiang, James Cheng:
Improving resource utilization by timely fine-grained scheduling. EuroSys 2020: 20:1-20:16 - [c77]Yifan Hou
Measuring and Improving the Use of Graph Information in Graph Neural Networks. ICLR 2020 - [c76]Qinghua Ding, Kaiwen Zhou, James Cheng:
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation. IJCAI 2020: 3276-3282 - [c75]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates. NeurIPS 2020 - [c74]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang
Convolutional Embedding for Edit Distance. SIGIR 2020: 599-608 - [c73]Hongzhi Chen, Bowen Wu, Shiyuan Deng, Chenghuan Huang, Changji Li
High Performance Distributed OLAP on Property Graphs with Grasper. SIGMOD Conference 2020: 2705-2708 - [c72]Kaiwen Zhou, Yanghua Jin, Qinghua Ding, James Cheng:
Amortized Nesterov's Momentum: A Robust Momentum and Its Application to Deep Learning. UAI 2020: 211-220 - [c71]Yitong Meng, Xiao Yan, Weiwen Liu
Wasserstein Collaborative Filtering for Item Cold-start Recommendation. UMAP 2020: 318-322 - [i42]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng:
Edit Distance Embedding using Convolutional Neural Networks. CoRR abs/2001.11692 (2020) - [i41]Han Yang, Xiao Yan, Xinyan Dai, James Cheng:
Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs. CoRR abs/2002.07518 (2020) - [i40]Zhenkun Cai, Kaihao Ma, Xiao Yan, Yidi Wu, Yuzhen Huang, James Cheng, Teng Su, Fan Yu:
TensorOpt: Exploring the Tradeoffs in Distributed DNN Training with Auto-Parallelism. CoRR abs/2004.10856 (2020) - [i39]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Boosting First-order Methods by Shifting Objective: New Schemes with Faster Worst Case Rates. CoRR abs/2005.12061 (2020) - [i38]Guoji Fu, Yifan Hou
Understanding Graph Neural Networks from Graph Signal Denoising Perspectives. CoRR abs/2006.04386 (2020) - [i37]Haibo Xiu, Xiao Yan, Xiaoqiang Wang, James Cheng, Lei Cao:
Hierarchical Graph Matching Network for Graph Similarity Computation. CoRR abs/2006.16551 (2020) - [i36]Han Yang, Kaili Ma
Rethinking Graph Regularization For Graph Neural Networks. CoRR abs/2009.02027 (2020) - [i35]Yitong Meng, Jie Liu, Xiao Yan, James Cheng:
The item selection problem for user cold-start recommendation. CoRR abs/2010.14013 (2020)
2010 – 2019
- 2019
- [j37]Yuzhen Huang, Yingjie Shi, Zheng Zhong, Yihui Feng, James Cheng, Jiwei Li, Haochuan Fan, Chao Li, Tao Guan, Jingren Zhou:
Yugong: Geo-Distributed Data and Job Placement at Scale. Proc. VLDB Endow. 12(12): 2155-2169 (2019) - [c70]Kaiwen Zhou, Qinghua Ding, Fanhua Shang, James Cheng, Danli Li, Zhi-Quan Luo:
Direct Acceleration of SAGA using Sampled Negative Momentum. AISTATS 2019: 1602-1610 - [c69]Shiyuan Deng, Xiao Yan, Kelvin Kai Wing Ng, Chenyu Jiang, James Cheng:
Pyramid: A General Framework for Distributed Similarity Search on Large-scale Datasets. IEEE BigData 2019: 1066-1071 - [c68]Hongzhi Chen, Changji Li
Grasper: A High Performance Distributed System for OLAP on Property Graphs. SoCC 2019: 87-100 - [c67]Da Yan, James Cheng, Hongzhi Chen, Cheng Long, Purushotham V. Bangalore:
Lightweight Fault Tolerance in Pregel-Like Systems. ICPP 2019: 69:1-69:10 - [c66]Yifan Hou
A Representation Learning Framework for Property Graphs. KDD 2019: 65-73 - [c65]Hongzhi Chen, Xiaoxi Wang, Chenghuan Huang, Juncheng Fang, Yifan Hou
Large Scale Graph Mining with G-Miner. SIGMOD Conference 2019: 1881-1884 - [c64]Yuzhen Huang, Xiao Yan, Guanxian Jiang, Tatiana Jin, James Cheng, An Xu, Zhanhao Liu, Shuo Tu:
Tangram: Bridging Immutable and Mutable Abstractions for Distributed Data Analytics. USENIX ATC 2019: 191-206 - [i34]Shiyuan Deng, Xiao Yan, Kelvin Kai Wing Ng, Chenyu Jiang, James Cheng:
Pyramid: A General Framework for Distributed Similarity Search. CoRR abs/1906.10602 (2019) - [i33]Yidi Wu, Kaihao Ma, Xiao Yan, Zhi Liu, James Cheng:
Elastic deep learning in multi-tenant GPU cluster. CoRR abs/1909.11985 (2019) - [i32]Jie Liu, Xiao Yan, Xinyan Dai, Zhirong Li, James Cheng, Ming-Chang Yang:
Understanding and Improving Proximity Graph based Maximum Inner Product Search. CoRR abs/1909.13459 (2019) - [i31]Xinyan Dai, Xiao Yan, Kelvin Kai Wing Ng, Jie Liu, James Cheng:
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. CoRR abs/1911.04654 (2019) - [i30]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Han Yang, Kelvin Kai Wing Ng, James Cheng, Yu Fan:
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning. CoRR abs/1911.04655 (2019) - 2018
- [j36]Fanhua Shang
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. IEEE Trans. Pattern Anal. Mach. Intell. 40(9): 2066-2080 (2018) - [j35]Yuzhen Huang, Tatiana Jin, Yidi Wu, Zhenkun Cai, Xiao Yan, Fan Yang, Jinfeng Li, Yuying Guo, James Cheng:
FlexPS: Flexible Parallelism Control in Parameter Server Architecture. Proc. VLDB Endow. 11(5): 566-579 (2018) - [j34]Fanhua Shang
Fuzzy Double Trace Norm Minimization for Recommendation Systems. IEEE Trans. Fuzzy Syst. 26(4): 2039-2049 (2018) - [j33]Da Yan
GraphD: Distributed Vertex-Centric Graph Processing Beyond the Memory Limit. IEEE Trans. Parallel Distributed Syst. 29(1): 99-114 (2018) - [c63]Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin:
ASVRG: Accelerated Proximal SVRG. ACML 2018: 815-830 - [c62]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. AISTATS 2018: 1027-1036 - [c61]Hongzhi Chen, Miao Liu
G-Miner: an efficient task-oriented graph mining system. EuroSys 2018: 32:1-32:12 - [c60]Da Yan, Hongzhi Chen, James Cheng, Zhenkun Cai, Bin Shao:
Scalable De Novo Genome Assembly Using Pregel. ICDE 2018: 1216-1219 - [c59]Kaiwen Zhou, Fanhua Shang, James Cheng:
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. ICML 2018: 5975-5984 - [c58]Xiao Yan, Jinfeng Li, Xinyan Dai, Hongzhi Chen, James Cheng:
Norm-Ranging LSH for Maximum Inner Product Search. NeurIPS 2018: 2956-2965 - [c57]Jinfeng Li, Xiao Yan, Jie Zhang, An Xu, James Cheng, Jie Liu
A General and Efficient Querying Method for Learning to Hash. SIGMOD Conference 2018: 1333-1347 - [i29]Da Yan, Hongzhi Chen, James Cheng, Zhenkun Cai, Bin Shao:
Scalable De Novo Genome Assembly Using Pregel. CoRR abs/1801.04453 (2018) - [i28]Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. CoRR abs/1802.09932 (2018) - [i27]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. CoRR abs/1802.09933 (2018) - [i26]Fanhua Shang, Yuanyuan Liu, James Cheng:
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. CoRR abs/1803.00420 (2018) - [i25]Kaiwen Zhou, Fanhua Shang, James Cheng:
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. CoRR abs/1806.11027 (2018) - [i24]Xiao Yan, Jinfeng Li, Xinyan Dai, Hongzhi Chen, James Cheng:
Norm-Ranging LSH for Maximum Inner Product Search. CoRR abs/1809.08782 (2018) - [i23]Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin:
ASVRG: Accelerated Proximal SVRG. CoRR abs/1810.03105 (2018) - [i22]Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin:
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. CoRR abs/1810.05186 (2018) - [i21]Xiao Yan, Xinyan Dai, Jie Liu, Kaiwen Zhou, James Cheng:
Norm-Range Partition: A Univiseral Catalyst for LSH based Maximum Inner Product Search (MIPS). CoRR abs/1810.09104 (2018) - 2017
- [b1]Da Yan, Yuanyuan Tian, James Cheng:
Systems for Big Graph Analytics. Springer Briefs in Computer Science, Springer 2017, ISBN 978-3-319-58216-0, pp. 1-92 - [j32]Zhiqiang Xu, James Cheng, Xiaokui Xiao
Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering. Knowl. Inf. Syst. 53(1): 239-268 (2017) - [j31]Fan Yang, Fanhua Shang, Yuzhen Huang, James Cheng, Jinfeng Li, Yunjian Zhao, Ruihao Zhao:
LFTF: A Framework for Efficient Tensor Analytics at Scale. Proc. VLDB Endow. 10(7): 745-756 (2017) - [c56]Yuanyuan Liu, Fanhua Shang, James Cheng:
Accelerated Variance Reduced Stochastic ADMM. AAAI 2017: 2287-2293 - [c55]Qizhen Zhang, Hongzhi Chen, Da Yan, James Cheng, Boon Thau Loo
Architectural implications on the performance and cost of graph analytics systems. SoCC 2017: 40-51 - [c54]Huanhuan Wu, Yunjian Zhao, James Cheng, Da Yan:
Efficient Processing of Growing Temporal Graphs. DASFAA (2) 2017: 387-403 - [c53]Yuanyuan Liu, Fanhua Shang, James Cheng, Hong Cheng, Licheng Jiao:
Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds. NIPS 2017: 4868-4877 - [c52]Jinfeng Li, James Cheng, Fan Yang, Yuzhen Huang, Yunjian Zhao, Xiao Yan, Ruihao Zhao:
LoSHa: A General Framework for Scalable Locality Sensitive Hashing. SIGIR 2017: 635-644 - [c51]Fan Yang, Yuzhen Huang, Yunjian Zhao, Jinfeng Li, Guanxian Jiang, James Cheng:
The Best of Both Worlds: Big Data Programming with Both Productivity and Performance. SIGMOD Conference 2017: 1619-1622 - [i20]Fanhua Shang, Yuanyuan Liu, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Variance Reduced Stochastic Gradient Descent with Sufficient Decrease. CoRR abs/1703.06807 (2017) - [i19]Fanhua Shang, Yuanyuan Liu, James Cheng, Jiacheng Zhuo:
Fast Stochastic Variance Reduced Gradient Method with Momentum Acceleration for Machine Learning. CoRR abs/1703.07948 (2017) - [i18]Yuanyuan Liu, Fanhua Shang, James Cheng:
Accelerated Variance Reduced Stochastic ADMM. CoRR abs/1707.03190 (2017) - [i17]Da Yan, Hongzhi Chen, James Cheng, M. Tamer Özsu, Qizhen Zhang, John C. S. Lui:
G-thinker: Big Graph Mining Made Easier and Faster. CoRR abs/1709.03110 (2017) - 2016
- [j30]Fan Yang, Jinfeng Li, James Cheng:
Husky: Towards a More Efficient and Expressive Distributed Computing Framework. Proc. VLDB Endow. 9(5): 420-431 (2016) - [j29]Da Yan, James Cheng, M. Tamer Özsu
A General-Purpose Query-Centric Framework for Querying Big Graphs. Proc. VLDB Endow. 9(7): 564-575 (2016) - [j28]Huanhuan Wu, James Cheng, Yiping Ke
Efficient Algorithms for Temporal Path Computation. IEEE Trans. Knowl. Data Eng. 28(11): 2927-2942 (2016) - [j27]Yuanyuan Liu
Generalized Higher Order Orthogonal Iteration for Tensor Learning and Decomposition. IEEE Trans. Neural Networks Learn. Syst. 27(12): 2551-2563 (2016) - [j26]Yanyan Xu, James Cheng, Ada Wai-Chee Fu:
Distributed Maximal Clique Computation and Management. IEEE Trans. Serv. Comput. 9(1): 110-122 (2016) - [c50]Fanhua Shang, Yuanyuan Liu, James Cheng:
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. AAAI 2016: 2016-2022 - [c49]Fanhua Shang, Yuanyuan Liu, James Cheng:
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. AISTATS 2016: 620-629 - [c48]Cheng Chen, Hejun Wu, Dyce Jing Zhao, Da Yan, James Cheng:
SGraph: A Distributed Streaming System for Processing Big Graphs. BigCom 2016: 285-294 - [c47]Jinfeng Li, James Cheng, Yunjian Zhao, Fan Yang, Yuzhen Huang, Haipeng Chen, Ruihao Zhao:
A comparison of general-purpose distributed systems for data processing. IEEE BigData 2016: 378-383 - [c46]Huanhuan Wu, Yuzhen Huang, James Cheng, Jinfeng Li, Yiping Ke
Reachability and time-based path queries in temporal graphs. ICDE 2016: 145-156 - [c45]Yi Yang, Da Yan, Huanhuan Wu, James Cheng, Shuigeng Zhou, John C. S. Lui:
Diversified Temporal Subgraph Pattern Mining. KDD 2016: 1965-1974 - [c44]Qizhen Zhang, Da Yan, James Cheng:
Quegel: A General-Purpose System for Querying Big Graphs. SIGMOD Conference 2016: 2189-2192 - [c43]Da Yan, Yingyi Bu, Yuanyuan Tian, Amol Deshpande, James Cheng:
Big Graph Analytics Systems. SIGMOD Conference 2016: 2241-2243 - [c42]Luyang Wang, Pallab Bhattacharya, Yao-Min Chen, Shrinivas Joshi, James Cheng:
End-to-End Java Security Performance Enhancements for Oracle SPARC Servers. ICPE 2016: 159-166 - [i16]Da Yan, Yuzhen Huang, James Cheng, Huanhuan Wu:
Efficient Processing of Very Large Graphs in a Small Cluster. CoRR abs/1601.05590 (2016) - [i15]Huanhuan Wu, Yuzhen Huang, James Cheng, Jinfeng Li, Yiping Ke:
Efficient Processing of Reachability and Time-Based Path Queries in a Temporal Graph. CoRR abs/1601.05909 (2016) - [i14]Da Yan, James Cheng, Fan Yang:
Lightweight Fault Tolerance in Large-Scale Distributed Graph Processing. CoRR abs/1601.06496 (2016) - [i13]Da Yan, James Cheng, M. Tamer Özsu, Fan Yang, Yi Lu, John C. S. Lui, Qizhen Zhang, Wilfred Ng:
Quegel: A General-Purpose Query-Centric Framework for Querying Big Graphs. CoRR abs/1601.06497 (2016) - [i12]Fanhua Shang, Yuanyuan Liu, James Cheng:
Unified Scalable Equivalent Formulations for Schatten Quasi-Norms. CoRR abs/1606.00668 (2016) - [i11]Fanhua Shang, Yuanyuan Liu, James Cheng:
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. CoRR abs/1606.01245 (2016) - 2015
- [j25]Fanhua Shang, Yuanyuan Liu, Hanghang Tong
Robust bilinear factorization with missing and grossly corrupted observations. Inf. Sci. 307: 53-72 (2015) - [j24]Wenting Liu, Guangxia Li, James Cheng:
Fast PageRank approximation by adaptive sampling. Knowl. Inf. Syst. 42(1): 127-146 (2015) - [j23]Da Yan, James Cheng, Zhou Zhao, Wilfred Ng
Efficient location-based search of trajectories with location importance. Knowl. Inf. Syst. 45(1): 215-245 (2015) - [j22]Yuanyuan Liu
Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data. IEEE Trans. Cybern. 45(11): 2437-2448 (2015) - [c41]Huanhuan Wu, James Cheng, Yi Lu, Yiping Ke
Core decomposition in large temporal graphs. IEEE BigData 2015: 649-658 - [c40]Da Yan, James Cheng, Yi Lu, Wilfred Ng:
Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation. WWW 2015: 1307-1317 - [i10]Da Yan, James Cheng, Yi Lu, Wilfred Ng:
Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation. CoRR abs/1503.00626 (2015) - [i9]Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng:
Regularized Orthogonal Tensor Decompositions for Multi-Relational Learning. CoRR abs/1512.08120 (2015) - 2014
- [j21]Huanhuan Wu, James Cheng, Silu Huang, Yiping Ke
Path Problems in Temporal Graphs. Proc. VLDB Endow. 7(9): 721-732 (2014) - [j20]Da Yan, James Cheng, Kai Xing, Yi Lu, Wilfred Ng, Yingyi Bu:
Pregel Algorithms for Graph Connectivity Problems with Performance Guarantees. Proc. VLDB Endow. 7(14): 1821-1832 (2014) - [j19]Da Yan, James Cheng, Yi Lu, Wilfred Ng:
Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs. Proc. VLDB Endow. 7(14): 1981-1992 (2014) - [j18]Yi Lu, James Cheng, Da Yan, Huanhuan Wu:
Large-Scale Distributed Graph Computing Systems: An Experimental Evaluation. Proc. VLDB Endow. 8(3): 281-292 (2014) - [j17]Zhiqiang Xu, Yiping Ke
GBAGC: A General Bayesian Framework for Attributed Graph Clustering. ACM Trans. Knowl. Discov. Data 9(1): 5:1-5:43 (2014) - [j16]James Cheng, Zechao Shang, Hong Cheng, Haixun Wang, Jeffrey Xu Yu:
Efficient processing of k-hop reachability queries. VLDB J. 23(2): 227-252 (2014) - [c39]Fanhua Shang, Yuanyuan Liu, James Cheng:
Generalized Higher-Order Tensor Decomposition via Parallel ADMM. AAAI 2014: 1279-1285 - [c38]Jia Wang, Ada Wai-Chee Fu, James Cheng:
Rectangle Counting in Large Bipartite Graphs. BigData Congress 2014: 17-24 - [c37]Yanyan Xu, James Cheng, Ada Wai-Chee Fu, Yingyi Bu:
Distributed Maximal Clique Computation. BigData Congress 2014: 160-167 - [c36]Zhou Zhao, James Cheng, Furu Wei, Ming Zhou, Wilfred Ng
SocialTransfer: Transferring Social Knowledge for Cold-Start Cowdsourcing. CIKM 2014: 779-788 - [c35]Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng:
Robust Principal Component Analysis with Missing Data. CIKM 2014: 1149-1158 - [c34]Zhou Zhao, James Cheng, Wilfred Ng
Truth Discovery in Data Streams: A Single-Pass Probabilistic Approach. CIKM 2014: 1589-1598 - [c33]Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng:
Recovering Low-Rank and Sparse Matrices via Robust Bilateral Factorization. ICDM 2014: 965-970 - [c32]Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng:
Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion. NIPS 2014: 1763-1771 - [c31]Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng, Hanghang Tong
Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion. SDM 2014: 866-874 - [c30]Linhong Zhu, Aram Galstyan, James Cheng, Kristina Lerman:
Tripartite graph clustering for dynamic sentiment analysis on social media. SIGMOD Conference 2014: 1531-1542 - [c29]Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng:
Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds. UAI 2014: 515-524 - [i8]Silu Huang, James Cheng, Huanhuan Wu:
Temporal Graph Traversals: Definitions, Algorithms, and Applications. CoRR abs/1401.1919 (2014) - [i7]Linhong Zhu, Aram Galstyan, James Cheng, Kristina Lerman:
Tripartite Graph Clustering for Dynamic Sentiment Analysis on Social Media. CoRR abs/1402.6010 (2014) - [i6]Minhao Jiang, Ada Wai-Chee Fu, Raymond Chi-Wing Wong, James Cheng, Yanyan Xu:
Hop Doubling Label Indexing for Point-to-Point Distance Querying on Scale-Free Networks. CoRR abs/1403.0779 (2014) - [i5]Fanhua Shang, Yuanyuan Liu, James Cheng:
Generalized Higher-Order Tensor Decomposition via Parallel ADMM. CoRR abs/1407.1399 (2014) - [i4]Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng:
Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations. CoRR abs/1409.1062 (2014) - 2013
- [j15]Ada Wai-Chee Fu, Huanhuan Wu, James Cheng, Raymond Chi-Wing Wong
IS-LABEL: an Independent-Set based Labeling Scheme for Point-to-Point Distance Querying. Proc. VLDB Endow. 6(6): 457-468 (2013) - [c28]Da Yan, James Cheng, Wilfred Ng
Finding distance-preserving subgraphs in large road networks. ICDE 2013: 625-636 - [c27]Jia Wang, James Cheng, Ada Wai-Chee Fu:
Redundancy-aware maximal cliques. KDD 2013: 122-130 - [c26]James Cheng, Silu Huang, Huanhuan Wu, Ada Wai-Chee Fu:
TF-Label: a topological-folding labeling scheme for reachability querying in a large graph. SIGMOD Conference 2013: 193-204 - 2012
- [j14]Jia Wang, James Cheng:
Truss Decomposition in Massive Networks. Proc. VLDB Endow. 5(9): 812-823 (2012) - [j13]James Cheng, Zechao Shang, Hong Cheng, Haixun Wang, Jeffrey Xu Yu:
K-Reach: Who is in Your Small World. Proc. VLDB Endow. 5(11): 1292-1303 (2012) - [j12]Shumo Chu, James Cheng:
Triangle listing in massive networks. ACM Trans. Knowl. Discov. Data 6(4): 17:1-17:32 (2012) - [c25]Wenqing Lin
Efficient algorithms for generalized subgraph query processing. CIKM 2012: 325-334 - [c24]James Cheng, Linhong Zhu, Yiping Ke
Fast algorithms for maximal clique enumeration with limited memory. KDD 2012: 1240-1248 - [c23]James Cheng, Yiping Ke
Efficient processing of distance queries in large graphs: a vertex cover approach. SIGMOD Conference 2012: 457-468 - [c22]Zhiqiang Xu, Yiping Ke
A model-based approach to attributed graph clustering. SIGMOD Conference 2012: 505-516 - [i3]Jia Wang, James Cheng:
Truss Decomposition in Massive Networks. CoRR abs/1205.6693 (2012) - [i2]James Cheng, Zechao Shang, Hong Cheng, Haixun Wang, Jeffrey Xu Yu:
K-Reach: Who is in Your Small World. CoRR abs/1208.0090 (2012) - [i1]Ada Wai-Chee Fu, Huanhuan Wu, James Cheng, Shumo Chu, Raymond Chi-Wing Wong:
IS-LABEL: an Independent-Set based Labeling Scheme for Point-to-Point Distance Querying on Large Graphs. CoRR abs/1211.2367 (2012) - 2011
- [j11]Linhong Zhu, Wee Keong Ng
Structure and attribute index for approximate graph matching in large graphs. Inf. Syst. 36(6): 958-972 (2011) - [j10]James Cheng, Yiping Ke
Finding maximal cliques in massive networks. ACM Trans. Database Syst. 36(4): 21:1-21:34 (2011) - [j9]James Cheng, Yiping Ke
Fast graph query processing with a low-cost index. VLDB J. 20(4): 521-539 (2011) - [c21]James Cheng, Yiping Ke
Efficient core decomposition in massive networks. ICDE 2011: 51-62 - [c20]Shumo Chu, James Cheng:
Triangle listing in massive networks and its applications. KDD 2011: 672-680 - 2010
- [c19]Yiping Ke
Querying Large Graph Databases. DASFAA (2) 2010: 487-488 - [c18]Changjiu Jin, Sourav S. Bhowmick
GBLENDER: towards blending visual query formulation and query processing in graph databases. SIGMOD Conference 2010: 111-122 - [c17]James Cheng, Yiping Ke
Finding maximal cliques in massive networks by H*-graph. SIGMOD Conference 2010: 447-458 - [c16]James Cheng, Ada Wai-Chee Fu, Jia Liu:
K-isomorphism: privacy preserving network publication against structural attacks. SIGMOD Conference 2010: 459-470
2000 – 2009
- 2009
- [j8]James Cheng, Yiping Ke
Efficient query processing on graph databases. ACM Trans. Database Syst. 34(1): 2:1-2:48 (2009) - [c15]James Cheng, Yiping Ke
Efficient processing of group-oriented connection queries in a large graph. CIKM 2009: 1481-1484 - [c14]James Cheng, Yiping Ke
Context-Aware Object Connection Discovery in Large Graphs. ICDE 2009: 856-867 - [c13]Yiping Ke
Efficient Discovery of Frequent Correlated Subgraph Pairs. ICDM 2009: 239-248 - [c12]Yiping Ke
Top-k Correlative Graph Mining. SDM 2009: 1038-1049 - 2008
- [j7]James Cheng, Yiping Ke
Effective elimination of redundant association rules. Data Min. Knowl. Discov. 16(2): 221-249 (2008) - [j6]James Cheng, Yiping Ke
Maintaining frequent closed itemsets over a sliding window. J. Intell. Inf. Syst. 31(3): 191-215 (2008) - [j5]James Cheng, Yiping Ke
A survey on algorithms for mining frequent itemsets over data streams. Knowl. Inf. Syst. 16(1): 1-27 (2008) - [j4]Yiping Ke
An information-theoretic approach to quantitative association rule mining. Knowl. Inf. Syst. 16(2): 213-244 (2008) - [j3]Yiping Ke
Efficient Correlation Search from Graph Databases. IEEE Trans. Knowl. Data Eng. 20(12): 1601-1615 (2008) - [j2]Yiping Ke
Correlated pattern mining in quantitative databases. ACM Trans. Database Syst. 33(3): 14:1-14:45 (2008) - 2007
- [c11]Wilfred Ng, James Cheng:
An Efficient Index Lattice for XML Query Evaluation. DASFAA 2007: 753-767 - [c10]James Cheng, Wilfred Ng:
A Development of Hash-Lookup Trees to Support Querying Streaming XML. DASFAA 2007: 768-780 - [c9]An Lu, Yiping Ke
Mining Vague Association Rules. DASFAA 2007: 891-897 - [c8]Yiping Ke
Correlation search in graph databases. KDD 2007: 390-399 - [c7]James Cheng, Yiping Ke
Fg-index: towards verification-free query processing on graph databases. SIGMOD Conference 2007: 857-872 - 2006
- [j1]Wilfred Ng
Comparative Analysis of XML Compression Technologies. World Wide Web 9(1): 5-33 (2006) - [c6]Yin Yang, Wilfred Ng, Ho Lam Lau, James Cheng:
An Efficient Approach to Support Querying Secure Outsourced XML Information. CAiSE 2006: 157-171 - [c5]Yiping Ke
MIC Framework: An Information-Theoretic Approach to Quantitative Association Rule Mining. ICDE 2006: 112 - [c4]James Cheng, Yiping Ke
delta-Tolerance Closed Frequent Itemsets. ICDM 2006: 139-148 - [c3]Yiping Ke
Mining quantitative correlated patterns using an information-theoretic approach. KDD 2006: 227-236 - [c2]James Cheng, Yiping Ke
Maintaining Frequent Itemsets over High-Speed Data Streams. PAKDD 2006: 462-467 - 2004
- [c1]James Cheng, Wilfred Ng:
XQzip: Querying Compressed XML Using Structural Indexing. EDBT 2004: 219-236
Coauthor Index
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