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2020 – today
- 2024
- [c125]Zhen Tan, Tianlong Chen, Zhenyu Zhang, Huan Liu:
Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention. AAAI 2024: 21619-21627 - [c124]Xin Juan, Kaixiong Zhou, Ninghao Liu, Tianlong Chen, Xin Wang:
Molecular Data Programming: Towards Molecule Pseudo-labeling with Systematic Weak Supervision. CVPR 2024: 308-318 - [c123]Yushi Huang, Ruihao Gong, Jing Liu, Tianlong Chen, Xianglong Liu:
TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models. CVPR 2024: 7362-7371 - [c122]Dawei Li, Zhen Tan, Tianlong Chen, Huan Liu:
Contextualization Distillation from Large Language Model for Knowledge Graph Completion. EACL (Findings) 2024: 458-477 - [c121]Yifan Li, Anh Dao, Wentao Bao, Zhen Tan, Tianlong Chen, Huan Liu, Yu Kong:
Facial Affective Behavior Analysis with Instruction Tuning. ECCV (18) 2024: 165-186 - [c120]Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen:
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy. ICLR 2024 - [c119]Xinyu Zhao, Xuxi Chen, Yu Cheng, Tianlong Chen:
Sparse MoE with Language Guided Routing for Multilingual Machine Translation. ICLR 2024 - [c118]Guanjie Chen, Xinyu Zhao, Tianlong Chen, Yu Cheng:
MoE-RBench: Towards Building Reliable Language Models with Sparse Mixture-of-Experts. ICML 2024 - [c117]Chengyue Gong, Adam R. Klivans, James Loy, Tianlong Chen, Qiang Liu, Daniel Jesus Diaz:
Evolution-Inspired Loss Functions for Protein Representation Learning. ICML 2024 - [c116]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c115]Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang:
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once. ICML 2024 - [c114]Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen:
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. ICML 2024 - [c113]Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen:
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness. ICML 2024 - [c112]Wenqing Zheng, Brian M. Sadler, Fernando Gama, Tianlong Chen:
Distributed UAV Beamforming Using Graph Recurrent Neural Networks. SAM 2024: 1-5 - [c111]Jinhao Duan, Shiqi Wang, James Diffenderfer, Lichao Sun, Tianlong Chen, Bhavya Kailkhura, Kaidi Xu:
ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models. NAACL-HLT 2024: 2232-2246 - [c110]Chi-Yang Hsu
, Kyle Cox
Thought Graph: Generating Thought Process for Biological Reasoning. WWW (Companion Volume) 2024: 537-540 - [i132]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i131]Tianlong Chen, Zhenyu Zhang, Hanrui Wang, Jiaqi Gu, Zirui Li, David Z. Pan, Frederic T. Chong, Song Han, Zhangyang Wang:
QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits. CoRR abs/2401.05571 (2024) - [i130]Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen:
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness. CoRR abs/2402.01242 (2024) - [i129]Dawei Li, Zhen Tan, Tianlong Chen, Huan Liu:
Contextualization Distillation from Large Language Model for Knowledge Graph Completion. CoRR abs/2402.01729 (2024) - [i128]Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen:
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. CoRR abs/2402.11592 (2024) - [i127]Jinhao Duan, Renming Zhang, James Diffenderfer
GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations. CoRR abs/2402.12348 (2024) - [i126]Lichi Li, Zainul Abi Din, Zhen Tan, Sam London, Tianlong Chen, Ajay H. Daptardar:
MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems. CoRR abs/2402.14230 (2024) - [i125]Zhiyuan Wang, Jinhao Duan, Chenxi Yuan, Qingyu Chen, Tianlong Chen, Huaxiu Yao, Yue Zhang, Ren Wang, Kaidi Xu, Xiaoshuang Shi:
Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond. CoRR abs/2402.14259 (2024) - [i124]Xuxi Chen, Zhendong Wang, Daouda Sow, Junjie Yang, Tianlong Chen, Yingbin Liang, Mingyuan Zhou, Zhangyang Wang:
Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization. CoRR abs/2402.14270 (2024) - [i123]Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Yu Kong, Tianlong Chen, Huan Liu:
The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative. CoRR abs/2402.14859 (2024) - [i122]Song Wang, Zhen Tan, Xinyu Zhao, Tianlong Chen, Huan Liu, Jundong Li:
GraphRCG: Self-conditioned Graph Generation via Bootstrapped Representations. CoRR abs/2403.01071 (2024) - [i121]Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei:
Privacy-preserving Fine-tuning of Large Language Models through Flatness. CoRR abs/2403.04124 (2024) - [i120]Zhen Tan, Jie Peng, Tianlong Chen, Huan Liu:
Tuning-Free Accountable Intervention for LLM Deployment - A Metacognitive Approach. CoRR abs/2403.05636 (2024) - [i119]Chi-Yang Hsu, Kyle Cox, Jiawei Xu, Zhen Tan, Tianhua Zhai, Mengzhou Hu
Thought Graph: Generating Thought Process for Biological Reasoning. CoRR abs/2403.07144 (2024) - [i118]Taishi Nakamura, Mayank Mishra, Simone Tedeschi, Yekun Chai, Jason T. Stillerman, Felix Friedrich, Prateek Yadav, Tanmay Laud, Minh Chien Vu, Terry Yue Zhuo, Diganta Misra, Ben Bogin, Xuan-Son Vu, Marzena Karpinska, Arnav Varma Dantuluri, Wojciech Kusa, Tommaso Furlanello, Rio Yokota, Niklas Muennighoff, Suhas Pai, Tosin P. Adewumi, Veronika Laippala, Xiaozhe Yao, Adalberto Junior, Alpay Ariyak, Aleksandr Drozd, Jordan Clive, Kshitij Gupta, Liangyu Chen, Qi Sun, Ken Tsui, Noah Persaud, Nour Moustafa-Fahmy, Tianlong Chen, Mohit Bansal, Nicolo Monti, Tai Dang, Ziyang Luo, Tien-Tung Bui, Roberto Navigli, Virendra Mehta, Matthew Blumberg, Victor May, Huu Nguyen, Sampo Pyysalo:
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order. CoRR abs/2404.00399 (2024) - [i117]Shwai He, Tianlong Chen:
RESSA: Repair Sparse Vision-Language Models via Sparse Cross-Modality Adaptation. CoRR abs/2404.02424 (2024) - [i116]Ajay Jaiswal, Bodun Hu, Lu Yin, Yeonju Ro, Shiwei Liu, Tianlong Chen, Aditya Akella:
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. CoRR abs/2404.03865 (2024) - [i115]Yifan Li, Anh Dao, Wentao Bao, Zhen Tan, Tianlong Chen, Huan Liu, Yu Kong:
Facial Affective Behavior Analysis with Instruction Tuning. CoRR abs/2404.05052 (2024) - [i114]Pingzhi Li, Junyu Liu, Hanrui Wang, Tianlong Chen:
Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent. CoRR abs/2405.00252 (2024) - [i113]Dawei Li, Shu Yang, Zhen Tan, Jae Young Baik, Sukwon Yun, Joseph Lee, Aaron Chacko, Bojian Hou, Duy Duong-Tran, Ying Ding, Huan Liu, Li Shen, Tianlong Chen:
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature. CoRR abs/2405.04819 (2024) - [i112]Guibin Zhang, Xiangguo Sun, Yanwei Yue, Kun Wang, Tianlong Chen, Shirui Pan:
Graph Sparsification via Mixture of Graphs. CoRR abs/2405.14260 (2024) - [i111]Pingzhi Li, Xiaolong Jin, Yu Cheng, Tianlong Chen:
Examining Post-Training Quantization for Mixture-of-Experts: A Benchmark. CoRR abs/2406.08155 (2024) - [i110]Guanjie Chen, Xinyu Zhao, Tianlong Chen, Yu Cheng:
MoE-RBench: Towards Building Reliable Language Models with Sparse Mixture-of-Experts. CoRR abs/2406.11353 (2024) - [i109]Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, Huan Liu:
"Glue pizza and eat rocks" - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models. CoRR abs/2406.19417 (2024) - [i108]Xinnan Zhang, Jialin Wu, Junyi Xie, Tianlong Chen, Kaixiong Zhou:
Benchmark on Drug Target Interaction Modeling from a Structure Perspective. CoRR abs/2407.04055 (2024) - [i107]Arinbjorn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen:
Composable Interventions for Language Models. CoRR abs/2407.06483 (2024) - [i106]Aditi Khandelwal, Harman Singh, Hengrui Gu, Tianlong Chen, Kaixiong Zhou:
Cross-Lingual Multi-Hop Knowledge Editing - Benchmarks, Analysis and a Simple Contrastive Learning based Approach. CoRR abs/2407.10275 (2024) - [i105]Zhen Tan, Daize Dong, Xinyu Zhao, Jie Peng, Yu Cheng, Tianlong Chen:
DLO: Dynamic Layer Operation for Efficient Vertical Scaling of LLMs. CoRR abs/2407.11030 (2024) - [i104]Bernardo Consoli, Xizhi Wu, Song Wang, Xinyu Zhao, Yanshan Wang, Justin F. Rousseau, Tom Hartvigsen, Li Shen, Huanmei Wu, Yifan Peng, Qi Long, Tianlong Chen, Ying Ding:
SDoH-GPT: Using Large Language Models to Extract Social Determinants of Health (SDoH). CoRR abs/2407.17126 (2024) - [i103]Tianjin Huang, Meng Fang, Li Shen, Fan Liu, Yulong Pei, Mykola Pechenizkiy, Shiwei Liu, Tianlong Chen:
(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork. CoRR abs/2407.17412 (2024) - [i102]Sukwon Yun, Jie Peng, Alexandro E. Trevino, Chanyoung Park, Tianlong Chen:
Mew: Multiplexed Immunofluorescence Image Analysis through an Efficient Multiplex Network. CoRR abs/2407.17857 (2024) - [i101]Prateek Yadav, Colin Raffel, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni:
A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning. CoRR abs/2408.07057 (2024) - [i100]Pingzhi Li, Tianlong Chen, Junyu Liu:
Enhancing Quantum Security over Federated Learning via Post-Quantum Cryptography. CoRR abs/2409.04637 (2024) - 2023
- [j18]Chaobo Li, Xiaokang Peng, Wei Shang
Formation Control of Spacecraft Based on SE(3) With Asymmetric Saturated Input. IEEE Access 11: 138856-138869 (2023) - [j17]Yan Han, Yuning You, Wenqing Zheng, Scott Hoang, Tianxin Wei, Majdi Hassan, Tianlong Chen, Ying Ding, Yang Shen, Zhangyang Wang:
Graph Contrastive Learning: An Odyssey towards Generalizable, Scalable and Principled Representation Learning on Graphs. IEEE Data Eng. Bull. 46(2): 80-95 (2023) - [j16]Shiwei Liu, Yuesong Tian, Tianlong Chen, Li Shen
Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance. Int. J. Comput. Vis. 131(10): 2635-2648 (2023) - [j15]Haotao Wang
Troubleshooting image segmentation models with human-in-the-loop. Mach. Learn. 112(3): 1033-1051 (2023) - [j14]Tianlong Chen
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 2769-2781 (2023) - [j13]Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang:
Can Pruning Improve Certified Robustness of Neural Networks? Trans. Mach. Learn. Res. 2023 (2023) - [c109]Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang:
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training. AAAI 2023: 8360-8368 - [c108]Xuxi Chen, Tianlong Chen, Weizhu Chen, Ahmed Hassan Awadallah, Zhangyang Wang, Yu Cheng:
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models. ACL (1) 2023: 8208-8222 - [c107]Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang:
Learning to Generalize Provably in Learning to Optimize. AISTATS 2023: 9807-9825 - [c106]Zhangheng Li, Yu Gong, Zhenyu Zhang, Xingyun Xue, Tianlong Chen, Yi Liang, Bo Yuan, Zhangyang Wang:
Accelerable Lottery Tickets with the Mixed-Precision Quantization. CVPR Workshops 2023: 4604-4612 - [c105]Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu:
Robust Mixture-of-Expert Training for Convolutional Neural Networks. ICCV 2023: 90-101 - [c104]Wenyan Cong, Hanxue Liang, Peihao Wang, Zhiwen Fan, Tianlong Chen, Mukund Varma T., Yi Wang, Zhangyang Wang:
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts. ICCV 2023: 3170-3181 - [c103]Tianlong Chen, Xuxi Chen, Xianzhi Du, Abdullah Rashwan, Fan Yang, Huizhong Chen, Zhangyang Wang, Yeqing Li:
AdaMV-MoE: Adaptive Multi-Task Vision Mixture-of-Experts. ICCV 2023: 17300-17311 - [c102]Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew D. Ellington, Alex Dimakis, Adam R. Klivans:
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing. ICLR 2023 - [c101]Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang:
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. ICLR 2023 - [c100]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang:
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR 2023 - [c99]Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang:
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR 2023 - [c98]Mukund Varma T., Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang:
Is Attention All That NeRF Needs? ICLR 2023 - [c97]Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang:
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation. ICLR 2023 - [c96]Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
Graph Domain Adaptation via Theory-Grounded Spectral Regularization. ICLR 2023 - [c95]Xuxi Chen, Nelson Vadori, Tianlong Chen, Zhangyang Wang:
Learning to Optimize Differentiable Games. ICML 2023: 5036-5051 - [c94]Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. ICML 2023: 14679-14690 - [c93]Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. ICML 2023: 14691-14701 - [c92]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang:
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. NeurIPS 2023 - [c91]Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen:
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. NeurIPS 2023 - [c90]Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy:
Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) 2023: 113-130 - [c89]Tianlong Chen, Zhenyu Zhang, Hanrui Wang, Jiaqi Gu, Zirui Li, David Z. Pan, Frederic T. Chong, Song Han, Zhangyang Wang:
QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits. QCE 2023: 51-62 - [c88]Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances. WACV 2023: 4976-4985 - [i99]Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang:
Learning to Generalize Provably in Learning to Optimize. CoRR abs/2302.11085 (2023) - [i98]Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang:
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation. CoRR abs/2303.00039 (2023) - [i97]Tianlong Chen, Zhenyu Zhang, Ajay Jaiswal, Shiwei Liu, Zhangyang Wang:
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. CoRR abs/2303.01610 (2023) - [i96]Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang:
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! CoRR abs/2303.02141 (2023) - [i95]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang:
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. CoRR abs/2306.03805 (2023) - [i94]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. CoRR abs/2306.10460 (2023) - [i93]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. CoRR abs/2306.10466 (2023) - [i92]Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen:
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. CoRR abs/2306.14048 (2023) - [i91]Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy:
Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR abs/2306.14275 (2023) - [i90]Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu:
Robust Mixture-of-Expert Training for Convolutional Neural Networks. CoRR abs/2308.10110 (2023) - [i89]Wenyan Cong, Hanxue Liang, Peihao Wang, Zhiwen Fan, Tianlong Chen, Mukund Varma T., Yi Wang, Zhangyang Wang:
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts. CoRR abs/2308.11793 (2023) - [i88]Pingzhi Li
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy. CoRR abs/2310.01334 (2023) - [i87]Yun Zhu, Nevan Wichers, Chu-Cheng Lin, Xinyi Wang, Tianlong Chen, Lei Shu, Han Lu, Canoee Liu, Liangchen Luo, Jindong Chen, Lei Meng:
SiRA: Sparse Mixture of Low Rank Adaptation. CoRR abs/2311.09179 (2023) - [i86]Yushi Huang, Ruihao Gong
TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models. CoRR abs/2311.16503 (2023) - [i85]Junjie Yang, Tianlong Chen, Xuxi Chen, Zhangyang Wang, Yingbin Liang:
Rethinking PGD Attack: Is Sign Function Necessary? CoRR abs/2312.01260 (2023) - [i84]Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen:
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR abs/2312.01397 (2023) - [i83]Tianjin Huang, Tianlong Chen, Zhangyang Wang, Shiwei Liu:
The Counterattack of CNNs in Self-Supervised Learning: Larger Kernel Size might be All You Need. CoRR abs/2312.05695 (2023) - [i82]Zhen Tan, Tianlong Chen, Zhenyu Zhang, Huan Liu:
Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention. CoRR abs/2312.15033 (2023) - 2022
- [j12]Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin:
Learning to Optimize: A Primer and A Benchmark. J. Mach. Learn. Res. 23: 189:1-189:59 (2022) - [j11]Tianlong Chen, Yu Cheng, Zhe Gan, Jianfeng Wang, Lijuan Wang, Jingjing Liu, Zhangyang Wang:
Adversarial Feature Augmentation and Normalization for Visual Recognition. Trans. Mach. Learn. Res. 2022 (2022) - [j10]Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang:
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning. Trans. Mach. Learn. Res. 2022 (2022) - [j9]Tianlong Chen, Zhenyu Zhang, Jun Wu, Randy Huang, Sijia Liu, Shiyu Chang, Zhangyang Wang:
Can You Win Everything with A Lottery Ticket? Trans. Mach. Learn. Res. 2022 (2022) - [j8]Chaojian Li
DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference. ACM Trans. Design Autom. Electr. Syst. 27(5): 50:1-50:20 (2022) - [j7]Ting-Kuei Hu, Fernando Gama
Scalable Perception-Action-Communication Loops With Convolutional and Graph Neural Networks. IEEE Trans. Signal Inf. Process. over Networks 8: 12-24 (2022) - [c87]Zhe Gan, Yen-Chun Chen, Linjie Li, Tianlong Chen, Yu Cheng, Shuohang Wang, Jingjing Liu, Lijuan Wang, Zicheng Liu:
Playing Lottery Tickets with Vision and Language. AAAI 2022: 652-660 - [c86]Duc N. M. Hoang, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks. AutoML 2022: 4/1-16 - [c85]Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang:
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free. CVPR 2022: 588-599 - [c84]Zhiwen Fan, Tianlong Chen, Peihao Wang, Zhangyang Wang:
CADTransformer: Panoptic Symbol Spotting Transformer for CAD Drawings. CVPR 2022: 10976-10986 - [c83]Tianlong Chen, Zhenyu Zhang, Yu Cheng, Ahmed Awadallah, Zhangyang Wang:
The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy. CVPR 2022: 12010-12020 - [c82]Tianlong Chen, Peihao Wang, Zhiwen Fan, Zhangyang Wang:
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations. CVPR 2022: 15170-15181 - [c81]Hanxue Liang, Hehe Fan, Zhiwen Fan, Yi Wang, Tianlong Chen, Yu Cheng, Zhangyang Wang:
Point Cloud Domain Adaptation via Masked Local 3D Structure Prediction. ECCV (3) 2022: 156-172 - [c80]Ziyu Jiang, Tianlong Chen, Xuxi Chen, Yu Cheng, Luowei Zhou, Lu Yuan, Ahmed Awadallah, Zhangyang Wang:
DnA: Improving Few-Shot Transfer Learning with Low-Rank Decomposition and Alignment. ECCV (20) 2022: 239-256 - [c79]Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Chen, Ahmed Awadallah, Zhangyang Wang:
Scalable Learning to Optimize: A Learned Optimizer Can Train Big Models. ECCV (23) 2022: 389-405 - [c78]Mu Yang, Shaojin Ding, Tianlong Chen, Tong Wang, Zhangyang Wang:
Towards Lifelong Learning of Multilingual Text-to-Speech Synthesis. ICASSP 2022: 8022-8026 - [c77]Tianlong Chen, Zhenyu Zhang, Pengjun Wang, Santosh Balachandra, Haoyu Ma, Zehao Wang, Zhangyang Wang:
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training. ICLR 2022 - [c76]Shaojin Ding, Tianlong Chen, Zhangyang Wang:
Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable. ICLR 2022 - [c75]Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang:
Optimizer Amalgamation. ICLR 2022 - [c74]Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. ICLR 2022 - [c73]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy:
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. ICLR 2022 - [c72]Lu Miao, Xiaolong Luo, Tianlong Chen, Wuyang Chen, Dong Liu, Zhangyang Wang:
Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, And No Retraining. ICLR 2022 - [c71]Peihao Wang, Wenqing Zheng, Tianlong Chen, Zhangyang Wang:
Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice. ICLR 2022 - [c70]Yuning You, Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How. ICLR 2022 - [c69]Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang:
Unified Visual Transformer Compression. ICLR 2022 - [c68]Wenqing Zheng, Tianlong Chen, Ting-Kuei Hu, Zhangyang Wang:
Symbolic Learning to Optimize: Towards Interpretability and Scalability. ICLR 2022 - [c67]Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wang, Zhangyang Wang:
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets. ICML 2022: 3025-3039 - [c66]Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang:
Data-Efficient Double-Win Lottery Tickets from Robust Pre-training. ICML 2022: 3747-3759 - [c65]Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang:
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness. ICML 2022: 3760-3772 - [c64]Ajay Kumar Jaiswal, Haoyu Ma, Tianlong Chen, Ying Ding, Zhangyang Wang:
Training Your Sparse Neural Network Better with Any Mask. ICML 2022: 9833-9844 - [c63]William T. Redman, Tianlong Chen, Zhangyang Wang, Akshunna S. Dogra
Universality of Winning Tickets: A Renormalization Group Perspective. ICML 2022: 18483-18498 - [c62]Peihao Wang, Zhiwen Fan, Tianlong Chen, Zhangyang Wang:
Neural Implicit Dictionary Learning via Mixture-of-Expert Training. ICML 2022: 22613-22624 - [c61]Yongduo Sui, Tianlong Chen, Pengfei Xia, Shuyao Wang, Bin Li:
Towards Robust Detection and Segmentation Using Vertical and Horizontal Adversarial Training. IJCNN 2022: 1-8 - [c60]Tianlong Chen, Xuemei Cheng, Thomas Tsao:
Border Ownership, Category Selectivity and Beyond. ISVC (2) 2022: 27-38 - [c59]Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu:
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG 2022: 8 - [c58]Ruisi Cai, Zhenyu Zhang, Tianlong Chen, Xiaohan Chen, Zhangyang Wang:
Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets. NeurIPS 2022 - [c57]Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. NeurIPS 2022 - [c56]Ajay Jaiswal, Peihao Wang, Tianlong Chen, Justin F. Rousseau, Ying Ding, Zhangyang Wang:
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again. NeurIPS 2022 - [c55]Hanxue Liang, Zhiwen Fan, Rishov Sarkar, Ziyu Jiang, Tianlong Chen, Kai Zou, Yu Cheng, Cong Hao, Zhangyang Wang:
M³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design. NeurIPS 2022 - [c54]Mukund Varma T., Xuxi Chen, Zhenyu Zhang, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang:
Sparse Winning Tickets are Data-Efficient Image Recognizers. NeurIPS 2022 - [c53]Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang:
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative. NeurIPS 2022 - [c52]Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu:
Advancing Model Pruning via Bi-level Optimization. NeurIPS 2022 - [c51]Xinyu Gong, Wuyang Chen, Tianlong Chen, Zhangyang Wang:
Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity. WACV 2022: 2957-2967 - [c50]Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations. WSDM 2022: 1300-1309 - [i81]Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen:
Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations. CoRR abs/2201.01702 (2022) - [i80]Mengshu Sun, Haoyu Ma, Guoliang Kang, Yifan Jiang, Tianlong Chen, Xiaolong Ma, Zhangyang Wang, Yanzhi Wang:
VAQF: Fully Automatic Software-hardware Co-design Framework for Low-bit Vision Transformer. CoRR abs/2201.06618 (2022) - [i79]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy:
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. CoRR abs/2202.02643 (2022) - [i78]Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wang, Zhangyang Wang:
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets. CoRR abs/2202.04736 (2022) - [i77]Tianlong Chen, Zhenyu Zhang, Pengjun Wang, Santosh Balachandra, Haoyu Ma, Zehao Wang, Zhangyang Wang:
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training. CoRR abs/2202.09844 (2022) - [i76]Shiwei Liu, Yuesong Tian, Tianlong Chen, Li Shen:
Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance. CoRR abs/2203.02770 (2022) - [i75]Peihao Wang, Wenqing Zheng, Tianlong Chen, Zhangyang Wang:
Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice. CoRR abs/2203.05962 (2022) - [i74]Tianlong Chen, Zhenyu Zhang, Yu Cheng, Ahmed Awadallah, Zhangyang Wang:
The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy. CoRR abs/2203.06345 (2022) - [i73]Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang:
Optimizer Amalgamation. CoRR abs/2203.06474 (2022) - [i72]Wenqing Zheng, Tianlong Chen, Ting-Kuei Hu, Zhangyang Wang:
Symbolic Learning to Optimize: Towards Interpretability and Scalability. CoRR abs/2203.06578 (2022) - [i71]Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang:
Unified Visual Transformer Compression. CoRR abs/2203.08243 (2022) - [i70]Diganta Misra, Bharat Runwal, Tianlong Chen, Zhangyang Wang, Irina Rish:
APP: Anytime Progressive Pruning. CoRR abs/2204.01640 (2022) - [i69]Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang:
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free. CoRR abs/2205.11819 (2022) - [i68]Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang:
Data-Efficient Double-Win Lottery Tickets from Robust Pre-training. CoRR abs/2206.04762 (2022) - [i67]Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang:
Can pruning improve certified robustness of neural networks? CoRR abs/2206.07311 (2022) - [i66]Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang:
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness. CoRR abs/2206.07839 (2022) - [i65]Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang:
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning. CoRR abs/2206.07842 (2022) - [i64]Ajay Jaiswal, Haoyu Ma, Tianlong Chen, Ying Ding, Zhangyang Wang:
Training Your Sparse Neural Network Better with Any Mask. CoRR abs/2206.12755 (2022) - [i63]Tianlong Chen, Peihao Wang, Zhiwen Fan, Zhangyang Wang:
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations. CoRR abs/2207.01164 (2022) - [i62]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang:
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. CoRR abs/2207.03620 (2022) - [i61]Peihao Wang, Zhiwen Fan, Tianlong Chen, Zhangyang Wang:
Neural Implicit Dictionary via Mixture-of-Expert Training. CoRR abs/2207.03691 (2022) - [i60]Mukund Varma T., Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang:
Is Attention All NeRF Needs? CoRR abs/2207.13298 (2022) - [i59]Yi Wang, Zhiwen Fan, Tianlong Chen, Hehe Fan, Zhangyang Wang:
Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer? CoRR abs/2209.07026 (2022) - [i58]Tianxin Wei
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative. CoRR abs/2210.03801 (2022) - [i57]Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao
Advancing Model Pruning via Bi-level Optimization. CoRR abs/2210.04092 (2022) - [i56]Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. CoRR abs/2210.07494 (2022) - [i55]Ajay Jaiswal, Peihao Wang, Tianlong Chen, Justin F. Rousseau
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again. CoRR abs/2210.08122 (2022) - [i54]Hanxue Liang, Zhiwen Fan, Rishov Sarkar, Ziyu Jiang, Tianlong Chen, Kai Zou, Yu Cheng, Cong Hao, Zhangyang Wang:
M3ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design. CoRR abs/2210.14793 (2022) - [i53]Kaixiong Zhou, Zhenyu Zhang, Shengyuan Chen, Tianlong Chen, Xiao Huang
QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks. CoRR abs/2211.07379 (2022) - [i52]Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang:
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training. CoRR abs/2211.10801 (2022) - [i51]Tianjin Huang
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR abs/2211.15335 (2022) - [i50]Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances. CoRR abs/2212.02675 (2022) - 2021
- [j6]Wei Shang
Adaptive Fixed Time Nonsingular Terminal Sliding-Mode Control for Quadrotor Formation With Obstacle and Inter-Quadrotor Avoidance. IEEE Access 9: 60640-60657 (2021) - [j5]Cheng Zhang, Tianlong Chen
Adaptive Super-Twisting Distributed Formation Control of Multi-Quadrotor Under External Disturbance. IEEE Access 9: 148104-148117 (2021) - [j4]Jianneng Chen, Xianbing Bian, Liqun Chen, Tianlong Chen, Zhiwei Chen
Design and testing of a production line mechanism for continuous cutting and coring of broccoli. Comput. Electron. Agric. 191: 106505 (2021) - [c49]Lida Zhang, Xiaohan Chen, Tianlong Chen, Zhangyang Wang, Bobak J. Mortazavi:
DynEHR: Dynamic adaptation of models with data heterogeneity in electronic health records. BHI 2021: 1-4 - [c48]Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang:
"BNN - BN = ?": Training Binary Neural Networks Without Batch Normalization. CVPR Workshops 2021: 4619-4629 - [c47]Zhihua Wang, Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma
Troubleshooting Blind Image Quality Models in the Wild. CVPR 2021: 16256-16265 - [c46]Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang:
The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models. CVPR 2021: 16306-16316 - [c45]Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Zhangyang Wang, Alejandro Ribeiro
VGAI: End-to-End Learning of Vision-Based Decentralized Controllers for Robot Swarms. ICASSP 2021: 4900-4904 - [c44]Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang:
Robust Overfitting may be mitigated by properly learned smoothening. ICLR 2021 - [c43]Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang:
Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning. ICLR 2021 - [c42]Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen:
GANs Can Play Lottery Tickets Too. ICLR 2021 - [c41]Haoyu Ma
Undistillable: Making A Nasty Teacher That CANNOT teach students. ICLR 2021 - [c40]Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang:
Learning A Minimax Optimizer: A Pilot Study. ICLR 2021 - [c39]Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang:
A Unified Lottery Ticket Hypothesis for Graph Neural Networks. ICML 2021: 1695-1706 - [c38]Ziyu Jiang, Tianlong Chen, Bobak J. Mortazavi, Zhangyang Wang:
Self-Damaging Contrastive Learning. ICML 2021: 4927-4939 - [c37]Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang:
Graph Contrastive Learning Automated. ICML 2021: 12121-12132 - [c36]Zhenyu Zhang, Xuxi Chen, Tianlong Chen, Zhangyang Wang:
Efficient Lottery Ticket Finding: Less Data is More. ICML 2021: 12380-12390 - [c35]Mingkang Zhu, Tianlong Chen, Zhangyang Wang:
Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm. ICML 2021: 12868-12877 - [c34]Xuxi Chen, Tianlong Chen, Zhenyu Zhang, Zhangyang Wang:
You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership. NeurIPS 2021: 1780-1791 - [c33]Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang:
Improving Contrastive Learning on Imbalanced Data via Open-World Sampling. NeurIPS 2021: 5997-6009 - [c32]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. NeurIPS 2021: 9908-9922 - [c31]Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang:
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? NeurIPS 2021: 12749-12760 - [c30]Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang:
Chasing Sparsity in Vision Transformers: An End-to-End Exploration. NeurIPS 2021: 19974-19988 - [c29]Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang:
Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective. NeurIPS 2021: 20941-20955 - [i49]Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang:
Good Students Play Big Lottery Better. CoRR abs/2101.03255 (2021) - [i48]Tianlong Chen, Yongduo Sui, Xuxi Chen
A Unified Lottery Ticket Hypothesis for Graph Neural Networks. CoRR abs/2102.06790 (2021) - [i47]Xinyu Gong, Wuyang Chen, Tianlong Chen, Zhangyang Wang:
Sandwich Batch Normalization. CoRR abs/2102.11382 (2021) - [i46]Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang:
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly. CoRR abs/2103.00397 (2021) - [i45]Tianlong Chen, Yu Cheng, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zhangyang Wang, Jingjing Liu:
Adversarial Feature Augmentation and Normalization for Visual Recognition. CoRR abs/2103.12171 (2021) - [i44]Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin:
Learning to Optimize: A Primer and A Benchmark. CoRR abs/2103.12828 (2021) - [i43]Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang:
"BNN - BN = ?": Training Binary Neural Networks without Batch Normalization. CoRR abs/2104.08215 (2021) - [i42]Arman Maesumi, Mingkang Zhu, Yi Wang, Tianlong Chen, Zhangyang Wang, Chandrajit Bajaj
Learning Transferable 3D Adversarial Cloaks for Deep Trained Detectors. CoRR abs/2104.11101 (2021) - [i41]Zhe Gan, Yen-Chun Chen, Linjie Li, Tianlong Chen, Yu Cheng, Shuohang Wang, Jingjing Liu:
Playing Lottery Tickets with Vision and Language. CoRR abs/2104.11832 (2021) - [i40]Zhihua Wang, Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma:
Troubleshooting Blind Image Quality Models in the Wild. CoRR abs/2105.06747 (2021) - [i39]Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang:
Undistillable: Making A Nasty Teacher That CANNOT teach students. CoRR abs/2105.07381 (2021) - [i38]Xuxi Chen
GANs Can Play Lottery Tickets Too. CoRR abs/2106.00134 (2021) - [i37]Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang:
Self-Damaging Contrastive Learning. CoRR abs/2106.02990 (2021) - [i36]Zhenyu Zhang, Xuxi Chen, Tianlong Chen, Zhangyang Wang:
Efficient Lottery Ticket Finding: Less Data is More. CoRR abs/2106.03225 (2021) - [i35]Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang:
Chasing Sparsity in Vision Transformers: An End-to-End Exploration. CoRR abs/2106.04533 (2021) - [i34]Mingkang Zhu, Tianlong Chen, Zhangyang Wang:
Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm. CoRR abs/2106.06027 (2021) - [i33]Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang:
Graph Contrastive Learning Automated. CoRR abs/2106.07594 (2021) - [i32]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. CoRR abs/2106.10404 (2021) - [i31]Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Wenqing Zheng, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler:
Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks. CoRR abs/2106.13358 (2021) - [i30]Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu
FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. CoRR abs/2106.14568 (2021) - [i29]Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang:
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? CoRR abs/2107.00166 (2021) - [i28]Chaojian Li, Wuyang Chen, Yuchen Gu, Tianlong Chen, Yonggan Fu, Zhangyang Wang, Yingyan Lin:
DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference. CoRR abs/2107.07706 (2021) - [i27]Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang:
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. CoRR abs/2108.10521 (2021) - [i26]William T. Redman
Universality of Deep Neural Network Lottery Tickets: A Renormalization Group Perspective. CoRR abs/2110.03210 (2021) - [i25]Mu Yang, Shaojin Ding, Tianlong Chen, Tong Wang, Zhangyang Wang:
Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis. CoRR abs/2110.04482 (2021) - [i24]Haotian Xue, Kaixiong Zhou, Tianlong Chen, Kai Guo, Xia Hu, Yi Chang, Xin Wang:
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks. CoRR abs/2110.14855 (2021) - [i23]Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Chen, Zhangyang Wang, Ahmed Hassan Awadallah:
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models. CoRR abs/2111.00160 (2021) - [i22]Xuxi Chen, Tianlong Chen, Zhenyu Zhang, Zhangyang Wang:
You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership. CoRR abs/2111.00162 (2021) - [i21]Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang:
Improving Contrastive Learning on Imbalanced Seed Data via Open-World Sampling. CoRR abs/2111.01004 (2021) - 2020
- [j3]Guowei Zhang
Multi-Layer Adaptive Finite Time Super Twisting Control for Quaternion-Based Quadrotor Formation With Obstacle Avoidance. IEEE Access 8: 213062-213077 (2020) - [j2]Anna M. Nia
Efficient identification of multiple pathways: RNA-Seq analysis of livers from 56Fe ion irradiated mice. BMC Bioinform. 21(1): 118 (2020) - [c28]Jiabo Chen, Tianlong Chen, Bin Xiao, Xiuli Bi, Yongchao Wang, Han Duan, Weisheng Li, Junhui Zhang, Xu Ma:
SE-ECGNet: Multi-scale SE-Net for Multi-lead ECG Data. CinC 2020: 1-4 - [c27]Tianlong Chen, Sijia Liu, Shiyu Chang, Yu Cheng, Lisa Amini, Zhangyang Wang:
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning. CVPR 2020: 696-705 - [c26]Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen:
L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks. CVPR 2020: 2124-2132 - [c25]Prateek Shroff, Tianlong Chen, Yunchao Wei, Zhangyang Wang:
Focus Longer to See Better: Recursively Refined Attention for Fine-Grained Image Classification. CVPR Workshops 2020: 3791-3798 - [c24]Chaojian Li, Tianlong Chen, Haoran You, Zhangyang Wang, Yingyan Lin:
HALO: Hardware-Aware Learning to Optimize. ECCV (9) 2020: 500-518 - [c23]Ting-Kuei Hu, Tianlong Chen, Haotao Wang, Zhangyang Wang:
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference. ICLR 2020 - [c22]Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma:
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively. ICLR 2020 - [c21]Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong, Kewei Chen, Zhangyang Wang:
Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training. ICML 2020: 1510-1519 - [c20]Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen:
When Does Self-Supervision Help Graph Convolutional Networks? ICML 2020: 10871-10880 - [c19]Shaojin Ding, Tianlong Chen, Xinyu Gong, Weiwei Zha, Zhangyang Wang:
AutoSpeech: Neural Architecture Search for Speaker Recognition. INTERSPEECH 2020: 916-920 - [c18]Xiaojing Yu, Tianlong Chen, Zhengjie Yu, Huiyu Li, Yang Yang, Xiaoqian Jiang, Anxiao Jiang:
Dataset and Enhanced Model for Eligibility Criteria-to-SQL Semantic Parsing. LREC 2020: 5829-5837 - [c17]Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin:
The Lottery Ticket Hypothesis for Pre-trained BERT Networks. NeurIPS 2020 - [c16]Tianlong Chen, Weiyi Zhang, Jingyang Zhou, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang:
Training Stronger Baselines for Learning to Optimize. NeurIPS 2020 - [c15]Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang:
Robust Pre-Training by Adversarial Contrastive Learning. NeurIPS 2020 - [c14]Haotao Wang, Tianlong Chen, Shupeng Gui, Ting-Kuei Hu, Ji Liu, Zhangyang Wang:
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free. NeurIPS 2020 - [c13]Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen:
Graph Contrastive Learning with Augmentations. NeurIPS 2020 - [c12]Ye Yuan, Wuyang Chen, Tianlong Chen, Yang Yang, Zhou Ren, Zhangyang Wang, Gang Hua:
Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification. WACV 2020: 3578-3587 - [i20]Ting-Kuei Hu, Tianlong Chen, Haotao Wang, Zhangyang Wang:
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference. CoRR abs/2002.10025 (2020) - [i19]Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma:
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively. CoRR abs/2002.10648 (2020) - [i18]Tianlong Chen, Sijia Liu, Shiyu Chang, Yu Cheng, Lisa Amini, Zhangyang Wang:
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning. CoRR abs/2003.12862 (2020) - [i17]Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen:
L^2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks. CoRR abs/2003.13606 (2020) - [i16]Shaojin Ding, Tianlong Chen, Xinyu Gong, Weiwei Zha, Zhangyang Wang:
AutoSpeech: Neural Architecture Search for Speaker Recognition. CoRR abs/2005.03215 (2020) - [i15]Prateek Shroff, Tianlong Chen, Yunchao Wei, Zhangyang Wang:
Focus Longer to See Better: Recursively Refined Attention for Fine-Grained Image Classification. CoRR abs/2005.10979 (2020) - [i14]Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen:
When Does Self-Supervision Help Graph Convolutional Networks? CoRR abs/2006.09136 (2020) - [i13]Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong, Kewei Chen, Zhangyang Wang:
Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training. CoRR abs/2006.11280 (2020) - [i12]Tianlong Chen, Yi Wang, Jingyang Zhou, Sijia Liu, Shiyu Chang, Chandrajit Bajaj, Zhangyang Wang:
Can 3D Adversarial Logos Cloak Humans? CoRR abs/2006.14655 (2020) - [i11]Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin:
The Lottery Ticket Hypothesis for Pre-trained BERT Networks. CoRR abs/2007.12223 (2020) - [i10]Yuli Zheng, Zhenyu Wu, Ye Yuan, Tianlong Chen, Zhangyang Wang:
PCAL: A Privacy-preserving Intelligent Credit Risk Modeling Framework Based on Adversarial Learning. CoRR abs/2010.02529 (2020) - [i9]Tianlong Chen, Weiyi Zhang, Jingyang Zhou, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang:
Training Stronger Baselines for Learning to Optimize. CoRR abs/2010.09089 (2020) - [i8]Haotao Wang, Tianlong Chen, Shupeng Gui, Ting-Kuei Hu, Ji Liu, Zhangyang Wang:
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free. CoRR abs/2010.11828 (2020) - [i7]Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang:
Robust Pre-Training by Adversarial Contrastive Learning. CoRR abs/2010.13337 (2020) - [i6]Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen:
Graph Contrastive Learning with Augmentations. CoRR abs/2010.13902 (2020) - [i5]Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang:
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models. CoRR abs/2012.06908 (2020)
2010 – 2019
- 2019
- [c11]Suresh K. Bhavnani, Clark Andersen, Yu-Li Lin, Emmanuel A. Santillana, Tianlong Chen, Yong-Fang Kuo:
The Role of Bipartite Networks in Stratified Predictive Modeling. AMIA 2019 - [c10]Tianlong Chen, Yu-Li Lin, I-Chia Liao, Yong-Fang Kuo, Emmanuel A. Santillana, Clark Andersen, Laurel A. Copeland, Suresh K. Bhavnani:
Bipartite Network Analysis with Multiple Datatypes: Implications for Precision Medicine in the Age of Multi-omics Data. AMIA 2019 - [c9]Tianlong Chen, Shaojin Ding, Jingyi Xie, Ye Yuan, Wuyang Chen, Yang Yang, Zhou Ren, Zhangyang Wang:
ABD-Net: Attentive but Diverse Person Re-Identification. ICCV 2019: 8350-8360 - [c8]Xiaojing Yu, Tianlong Chen, Yang Yang, Michael Mugo, Zhangyang Wang:
Cross-Modal Person Search: A Coarse-to-Fine Framework using Bi-Directional Text-Image Matching. ICCV Workshops 2019: 1799-1804 - [c7]Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen:
Learning to Optimize in Swarms. NeurIPS 2019: 15018-15028 - [i4]Tianlong Chen, Shaojin Ding, Jingyi Xie, Ye Yuan, Wuyang Chen, Yang Yang, Zhou Ren, Zhangyang Wang:
ABD-Net: Attentive but Diverse Person Re-Identification. CoRR abs/1908.01114 (2019) - [i3]Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen:
Learning to Optimize in Swarms. CoRR abs/1911.03787 (2019) - [i2]Ye Yuan, Wuyang Chen, Tianlong Chen, Yang Yang, Zhou Ren, Zhangyang Wang, Gang Hua:
Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification. CoRR abs/1911.11314 (2019) - 2018
- [c6]Suresh K. Bhavnani, Revathi Sellappan, Saurabh Joshi, Jonathan Starkey, Winston Chan, Tianlong Chen, Shyam Visweswaran:
Utility of Visual Analytics for Identifying Patient Subgroups in EMRs: Insights for Accelerating Precision Medicine. AMIA 2018 - 2017
- [c5]Suresh K. Bhavnani, Archana Ayyaswami, Tianlong Chen, Shyam Visweswaran, Gowtham Bellala, Kevin E. Bassler:
Vicinity Exploration: Enabling User-Driven Visual Search of Multiple Machine Learning Models for Precision Medicine. AMIA 2017 - [c4]Suresh K. Bhavnani, Archana Ayyaswami, Tianlong Chen, Jeremy L. Warner:
Identification of Patient Subgroups in Metastatic Breast Cancer Patients Based on Somatic Copy Number Alterations: A Bipartite Network Analysis. AMIA 2017 - [i1]Tianlong Chen, Pramesh Singh, Kevin E. Bassler:
Network community detection using modularity density measures. CoRR abs/1708.06810 (2017) - 2016
- [c3]Bryant Dang, Joseph Mathew, Tianlong Chen, Suresh K. Bhavnani:
ExplodeLayout: Comprehending Patient Subgroups in Large Networks. AMIA 2016 - 2015
- [j1]Weigang Zhang
Fusing cross-media for topic detection by dense keyword groups. Neurocomputing 169: 169-179 (2015) - 2012
- [c2]Tianlong Chen, Chunxi Liu, Qingming Huang:
An effective multi-clue fusion approach for web video topic detection. ACM Multimedia 2012: 781-784 - 2011
- [c1]Tianlong Chen, Shuqiang Jiang, Lingyang Chu, Qingming Huang:
Detection and location of near-duplicate video sub-clips by finding dense subgraphs. ACM Multimedia 2011: 1173-1176
Coauthor Index
Ajay Jaiswal
aka: Ajay Kumar Jaiswal
aka: Ajay Kumar Jaiswal
[c115] [c114] [i131] [i128] [i124] [j17] [j15] [j14] [j13] [c109] [c108] [c107] [c106] [c105] [c104] [c103] [c102] [c101] [c100] [c99] [c98] [c97] [c96] [c95] [c94] [c93] [c92] [c91] [c89] [c88] [i99] [i98] [i97] [i96] [i95] [i94] [i93] [i92] [i90] [i89] [i85] [i83] [j12] [j11] [j10] [j9] [j8] [j7] [c86] [c85] [c84] [c83] [c82] [c81] [c80] [c79] [c78] [c77] [c76] [c75] [c74] [c73] [c72] [c71] [c70] [c69] [c68] [c67] [c66] [c65] [c64] [c63] [c62] [c59] [c58] [c57] [c56] [c55] [c54] [c53] [c51] [c50] [i81] [i80] [i79] [i78] [i77] [i75] [i74] [i73] [i72] [i71] [i70] [i69] [i68] [i67] [i66] [i65] [i64] [i63] [i62] [i61] [i60] [i59] [i58] [i56] [i55] [i54] [i53] [i52] [i51] [i50] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [i49] [i48] [i47] [i46] [i45] [i44] [i43] [i42] [i40] [i39] [i37] [i36] [i35] [i34] [i33] [i32] [i31] [i30] [i29] [i28] [i27] [i26] [i25] [i23] [i22] [i21] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c17] [c16] [c15] [c14] [c13] [c12] [i20] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [c9] [c8] [c7] [i4] [i3] [i2]
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