Xiaohan Chen - RankMe

61 papers A* 24A 1Journal 31Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs. ICML Ziang Chen, Xiaohan Chen, Jialin Liu, Xinshang Wang, Wotao Yin
2024	J	`jnl`	Chasing Better Deep Image Priors between Over- and Under-parameterization. CoRR Qiming Wu, Xiaohan Chen, Yifan Jiang, Zhangyang Wang
2024	J	`jnl`	DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. Trans. Mach. Learn. Res. Haoyu Peter Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin
2024	J	`jnl`	Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs. CoRR Ziang Chen, Xiaohan Chen, Jialin Liu, Xinshang Wang, Wotao Yin
2024	J	`jnl`	Learning to optimize: A tutorial for continuous and mixed-integer optimization. CoRR Xiaohan Chen, Jialin Liu, Wotao Yin
2024	A*	`conf`	Rethinking the Capacity of Graph Neural Networks for Branching Strategy. NeurIPS Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin
2024	J	`jnl`	Rethinking the Capacity of Graph Neural Networks for Branching Strategy. CoRR Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin
2023	J	`jnl`	Chasing Better Deep Image Priors between Over- and Under-parameterization. Trans. Mach. Learn. Res. Qiming Wu, Xiaohan Chen, Yifan Jiang, Zhangyang Wang
2023	J	`jnl`	DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. CoRR Haoyu Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin
2023	—	`conf`	Many-Task Federated Learning: A New Problem Setting and A Simple Baseline. CVPR Workshops Ruisi Cai, Xiaohan Chen, Shiwei Liu, Jayanth Srinivasa, Myungjin Lee, Ramana Kompella, Zhangyang Wang
2023	A*	`conf`	More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
2023	A*	`conf`	Safeguarded Learned Convex Optimization. AAAI Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin
2023	J	`jnl`	SmartDeal: Remodeling Deep Network Weights for Efficient Inference and Training. IEEE Trans. Neural Networks Learn. Syst. Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang
2023	A*	`conf`	Towards Constituting Mathematical Structures for Learning to Optimize. ICML Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai
2023	J	`jnl`	Towards Constituting Mathematical Structures for Learning to Optimize. CoRR Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai
2022	A*	`conf`	Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. ICLR Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2022	A*	`conf`	Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better. AAAI Sameer Bibikar, Haris Vikalo, Zhangyang Wang, Xiaohan Chen
2022	J	`jnl`	Learning to Optimize: A Primer and A Benchmark. J. Mach. Learn. Res. Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin
2022	—	`conf`	Model elasticity for hardware heterogeneity in federated learning systems. FedEdge@MobiCom Allen-Jasmin Farcas, Xiaohan Chen, Zhangyang Wang, Radu Marculescu
2022	J	`jnl`	More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. CoRR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
2022	A*	`conf`	Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently. ICLR Xiaohan Chen, Jason Zhang, Zhangyang Wang
2022	A*	`conf`	Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets. NeurIPS Ruisi Cai, Zhenyu Zhang, Tianlong Chen, Xiaohan Chen, Zhangyang Wang
2022	A*	`conf`	The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. ICLR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
2022	J	`jnl`	The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. CoRR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
2021	A*	`conf`	A Design Space Study for LISTA and Beyond. ICLR Tianjian Meng, Xiaohan Chen, Yifan Jiang, Zhangyang Wang
2021	J	`jnl`	A Design Space Study for LISTA and Beyond. CoRR Tianjian Meng, Xiaohan Chen, Yifan Jiang, Zhangyang Wang
2021	—	`conf`	DynEHR: Dynamic adaptation of models with data heterogeneity in electronic health records. BHI Lida Zhang, Xiaohan Chen, Tianlong Chen, Zhangyang Wang, Bobak J. Mortazavi
2021	—	`conf`	EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets. ACL/IJCNLP (1) Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Zhangyang Wang, Jingjing Liu
2021	J	`jnl`	EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets. CoRR Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Zhangyang Wang, Jingjing Liu
2021	J	`jnl`	Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better. CoRR Sameer Bibikar, Haris Vikalo, Zhangyang Wang, Xiaohan Chen
2021	J	`jnl`	FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. CoRR Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2021	A*	`conf`	Hyperparameter Tuning is All You Need for LISTA. NeurIPS Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin
2021	J	`jnl`	Hyperparameter Tuning is All You Need for LISTA. CoRR Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin
2021	A*	`conf`	Learning A Minimax Optimizer: A Pilot Study. ICLR Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang
2021	J	`jnl`	Learning to Optimize: A Primer and A Benchmark. CoRR Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin
2021	A*	`conf`	Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? NeurIPS Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang
2021	J	`jnl`	Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? CoRR Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang
2021	J	`jnl`	SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training. CoRR Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang
2021	A*	`conf`	Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. NeurIPS Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2021	J	`jnl`	Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. CoRR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2021	A*	`conf`	The Elastic Lottery Ticket Hypothesis. NeurIPS Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Jingjing Liu, Zhangyang Wang
2021	J	`jnl`	The Elastic Lottery Ticket Hypothesis. CoRR Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Jingjing Liu, Zhangyang Wang
2020	A*	`conf`	Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks. ICLR Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin
2020	A*	`conf`	MATE: Plugging in Model Awareness to Task Embedding for Meta Learning. NeurIPS Xiaohan Chen, Zhangyang Wang, Siyu Tang, Krikamol Muandet
2020	J	`jnl`	Safeguarded Learned Convex Optimization. CoRR Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin
2020	A*	`conf`	ShiftAddNet: A Hardware-Inspired Deep Network. NeurIPS Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin
2020	J	`jnl`	ShiftAddNet: A Hardware-Inspired Deep Network. CoRR Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin
2020	A*	`conf`	SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. ISCA Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin
2020	J	`jnl`	SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. CoRR Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin
2020	A	`conf`	Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. AISTATS Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi
2020	J	`jnl`	Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. CoRR Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi
2019	—	`conf`	ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA. ICLR (Poster) Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin
2019	J	`jnl`	Drawing early-bird tickets: Towards more efficient training of deep networks. CoRR Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, Richard G. Baraniuk
2019	J	`jnl`	E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving. CoRR Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang
2019	A*	`conf`	E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings. NeurIPS Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang
2019	A*	`conf`	Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. ICML Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin
2019	J	`jnl`	Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. CoRR Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin
2018	J	`jnl`	Can We Gain More from Orthogonality Regularizations in Training Deep CNNs? CoRR Nitin Bansal, Xiaohan Chen, Zhangyang Wang
2018	A*	`conf`	Can We Gain More from Orthogonality Regularizations in Training Deep Networks? NeurIPS Nitin Bansal, Xiaohan Chen, Zhangyang Wang
2018	A*	`conf`	Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds. NeurIPS Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin
2018	J	`jnl`	Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds. CoRR Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin