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Learn to Predict Equilibria via Fixed Point Networks


Jun 02, 2021
Howard Heaton, Daniel McKenzie, Qiuwei Li, Samy Wu Fung, Stanley Osher, Wotao Yin


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Accelerating Gossip SGD with Periodic Global Averaging


May 19, 2021
Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin

* Accepted to ICML 2021 

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On Stochastic Moving-Average Estimators for Non-Convex Optimization


Apr 30, 2021
Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang


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Feasibility-based Fixed Point Networks


Apr 29, 2021
Howard Heaton, Samy Wu Fung, Aviv Gibali, Wotao Yin


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On the Comparison between Cyclic Sampling and Random Reshuffling


Apr 25, 2021
Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin


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DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training


Apr 24, 2021
Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin


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Learning to Optimize: A Primer and A Benchmark


Mar 23, 2021
Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin


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Fixed Point Networks: Implicit Depth Models with Jacobian-Free Backprop


Mar 23, 2021
Samy Wu Fung, Howard Heaton, Qiuwei Li, Daniel McKenzie, Stanley Osher, Wotao Yin


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Provably Correct Optimization and Exploration with Non-linear Policies


Mar 22, 2021
Fei Feng, Wotao Yin, Alekh Agarwal, Lin F. Yang


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A Single-Timescale Stochastic Bilevel Optimization Method


Feb 22, 2021
Tianyi Chen, Yuejiao Sun, Wotao Yin

* Minor edits in Table 1 

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A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization


Feb 21, 2021
HanQin Cai, Yuchen Lou, Daniel McKenzie, Wotao Yin


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CADA: Communication-Adaptive Distributed Adam


Dec 31, 2020
Tianyi Chen, Ziye Guo, Yuejiao Sun, Wotao Yin

* OPT2020: NeurIPS Workshop on Optimization for Machine Learning 

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Hybrid Federated Learning: Algorithms and Implementation


Dec 29, 2020
Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen


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Hybrid FL: Algorithms and Implementation


Dec 22, 2020
Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen


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Attentional Biased Stochastic Gradient for Imbalanced Classification


Dec 13, 2020
Qi Qi, Yi Xu, Rong Jin, Wotao Yin, Tianbao Yang

* 25pages, 10 figures 

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SCOBO: Sparsity-Aware Comparison Oracle Based Optimization


Oct 06, 2020
HanQin Cai, Daniel Mckenzie, Wotao Yin, Zhenliang Zhang


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Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization


Aug 31, 2020
Tianyi Chen, Yuejiao Sun, Wotao Yin

* Fixed typos in the proof 

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Projecting to Manifolds via Unsupervised Learning


Aug 05, 2020
Howard Heaton, Samy Wu Fung, Alex Tong Lin, Stanley Osher, Wotao Yin


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VAFL: a Method of Vertical Asynchronous Federated Learning


Jul 12, 2020
Tianyi Chen, Xiao Jin, Yuejiao Sun, Wotao Yin

* FL-ICML'20: Proc. of ICML Workshop on Federated Learning for User Privacy and Data Confidentiality, July 2020 

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FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data


May 26, 2020
Xinwei Zhang, Mingyi Hong, Sairaj Dhople, Wotao Yin, Yang Liu


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Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling


Mar 29, 2020
HanQin Cai, Daniel Mckenzie, Wotao Yin, Zhenliang Zhang


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Provably Efficient Exploration for RL with Unsupervised Learning


Mar 15, 2020
Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang


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Safeguarded Learned Convex Optimization


Mar 04, 2020
Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin


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LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning


Feb 26, 2020
Tianyi Chen, Yuejiao Sun, Wotao Yin


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Does Knowledge Transfer Always Help to Learn a Better Policy?


Dec 06, 2019
Fei Feng, Wotao Yin, Lin F. Yang


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XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training


Nov 20, 2019
Lei Guan, Wotao Yin, Dongsheng Li, Xicheng Lu

* 9 pages 

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ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs


Jun 06, 2019
Ernest K. Ryu, Kun Yuan, Wotao Yin


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