Xiaohan Chen

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Zhangyang (Atlas) WangXTX Markets & University of Texas at AustinAdresse e-mail validée de utexas.edu
Jialin LiuUniversity of Central FloridaAdresse e-mail validée de ucf.edu
Wotao YinDAMO Academy, Alibaba Group USAdresse e-mail validée de alibaba-inc.com
Tianlong ChenAssistant Professor, CS@UNC Chapel Hill; PostDoc, CSAIL@MIT+BMI@Harvard; Ph.D., ECE@UT AustinAdresse e-mail validée de cs.unc.edu
Yingyan (Celine) LinAssociate Professor, Georgia Institute of TechnologyAdresse e-mail validée de gatech.edu
Yue WangMagna InternationalAdresse e-mail validée de magna.com
Haoran YouGeorgia Institute of TechnologyAdresse e-mail validée de gatech.edu
Yang (Katie) ZhaoAssistant Professor, University of Minnesota, Twin CitiesAdresse e-mail validée de umn.edu
Yonggan FuGeorgia Institute of TechnologyAdresse e-mail validée de gatech.edu
Howard HeatonTypal AcademyAdresse e-mail validée de typal.academy
Ernest K. RyuUniversity of California, Los AngelesAdresse e-mail validée de math.ucla.edu
Nitin BansalStaff Engineer, Samsung ResearchAdresse e-mail validée de samsung.com
Richard BaraniukC. Sidney Burrus Professor, Electrical & Computer Engineering, Rice UniversityAdresse e-mail validée de rice.edu
Zhe GanResearch Scientist, AppleAdresse e-mail validée de apple.com
Yu ChengThe Chinese University of Hong KongAdresse e-mail validée de cse.cuhk.edu.hk
Shuohang WangPrincipal Researcher, Microsoft GenAIAdresse e-mail validée de microsoft.com
Wuyang ChenAssistant Professor, CS@Simon Fraser UniversityAdresse e-mail validée de sfu.ca
Bobak J. MortazaviComputer Science & Engineering, Texas A&MAdresse e-mail validée de tamu.edu
Ziyu JiangResearch Assistant, Texas A&M UniversityAdresse e-mail validée de tamu.edu
Yuan XieChair Professor of Hong Kong University of Science and Technology (HKUST)Adresse e-mail validée de ust.hk

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Xiaohan Chen

DAMO Academy, Alibaba Group

Adresse e-mail validée de utexas.edu - Page d'accueil

Sparse Optimization Inverse Problems Learning to Optimize Meta Learning Efficient Deep Learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Plug-and-play methods provably converge with properly trained denoisers E Ryu, J Liu, S Wang, X Chen, Z Wang, W Yin International Conference on Machine Learning, 5546-5557, 2019	431	2019
Can we gain more from orthogonality regularizations in training deep networks? N Bansal, X Chen, Z Wang Advances in Neural Information Processing Systems 31, 2018	383	2018
Drawing early-bird tickets: Towards more efficient training of deep networks H You, C Li, P Xu, Y Fu, Y Wang, X Chen, RG Baraniuk, Z Wang, Y Lin arXiv preprint arXiv:1909.11957, 2019	292	2019
Theoretical linear convergence of unfolded ISTA and its practical weights and thresholds X Chen, J Liu, Z Wang, W Yin Advances in Neural Information Processing Systems 31, 2018	285	2018
Learning to optimize: A primer and a benchmark T Chen, X Chen, W Chen, H Heaton, J Liu, Z Wang, W Yin Journal of Machine Learning Research 23 (189), 1-59, 2022	255	2022
ALISTA: Analytic weights are as good as learned weights in LISTA J Liu, X Chen International Conference on Learning Representations (ICLR), 2019	221	2019
More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity S Liu, T Chen, X Chen, X Chen, Q Xiao, B Wu, T Kärkkäinen, ... arXiv preprint arXiv:2207.03620, 2022	206	2022
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration S Liu, T Chen, X Chen, Z Atashgahi, L Yin, H Kou, L Shen, M Pechenizkiy, ... Neural Information Processing Systems 2021, 2021	132	2021
The unreasonable effectiveness of random pruning: Return of the most naive baseline for sparse training S Liu, T Chen, X Chen, L Shen, DC Mocanu, Z Wang, M Pechenizkiy arXiv preprint arXiv:2202.02643, 2022	123	2022
Federated dynamic sparse training: Computing less, communicating less, yet learning better S Bibikar, H Vikalo, Z Wang, X Chen Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6080-6088, 2022	108	2022
E2-train: Training state-of-the-art cnns with over 80% energy savings Y Wang, Z Jiang, X Chen, P Xu, Y Zhao, Y Lin, Z Wang Advances in Neural Information Processing Systems 32, 2019	108	2019
Shiftaddnet: A hardware-inspired deep network H You, X Chen, Y Zhang, C Li, S Li, Z Liu, Z Wang, Y Lin Advances in Neural Information Processing Systems 33, 2771-2783, 2020	96	2020
Earlybert: Efficient bert training via early-bird lottery tickets X Chen, Y Cheng, S Wang, Z Gan, Z Wang, J Liu arXiv preprint arXiv:2101.00063, 2020	94	2020
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? X Ma, G Yuan, X Shen, T Chen, X Chen, X Chen, N Liu, M Qin, S Liu, ... Neural Information Processing Systems 2021, 2021	66	2021
Deep ensembling with no overhead for either training or testing: The all-round blessings of dynamic sparsity S Liu, T Chen, Z Atashgahi, X Chen, G Sokar, E Mocanu, M Pechenizkiy, ... arXiv preprint arXiv:2106.14568, 2021	58	2021
Smartexchange: Trading higher-cost memory storage/access for lower-cost computation Y Zhao, X Chen, Y Wang, C Li, H You, Y Fu, Y Xie, Z Wang, Y Lin 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture …, 2020	53	2020
Learning a minimax optimizer: A pilot study J Shen, X Chen, H Heaton, T Chen, J Liu, W Yin, Z Wang International Conference on Learning Representations, 2020	32	2020
Safeguarded learned convex optimization H Heaton, X Chen, Z Wang, W Yin Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7848-7855, 2023	30	2023
The Elastic Lottery Ticket Hypothesis X Chen, Y Cheng, S Wang, Z Gan, J Liu, Z Wang Neural Information Processing Systems 2021, 2021	30	2021
Hyperparameter Tuning is All You Need for LISTA X Chen, J Liu, Z Wang, W Yin Neural Information Processing Systems 2021, 2021	28	2021

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