Wotao Yin

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 174

Top Venues

CoRR

NeurIPS

J. Sci. Comput.

IEEE Trans. Signal Process.

Publications

Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen
Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation. Trans. Mach. Learn. Res. 2024 (2024)
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 (2024)
Zhonglin Xie, Wotao Yin, Zaiwen Wen
ODE-based Learning to Optimize. CoRR (2024)
Huajie Qian, Donghao Ying, Henry Lam, Wotao Yin
Bagging Improves Generalization Exponentially. CoRR (2024)
Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin
Rethinking the Capacity of Graph Neural Networks for Branching Strategy. CoRR (2024)
Ziang Chen, Xiaohan Chen, Jialin Liu, Xinshang Wang, Wotao Yin
Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs. CoRR (2024)
Kaizhao Sun, Mou Sun, Wotao Yin
Decomposition Methods for Global Solution of Mixed-Integer Linear Programs. SIAM J. Optim. 34 (2) (2024)
Jihai Zhang, Wei Wang, Siyan Guo, Li Wang, Fangquan Lin, Cheng Yang, Wotao Yin
Solving General Natural-Language-Description Optimization Problems with Large Language Models. CoRR (2024)
Liangzu Peng, Wotao Yin
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares. CoRR (2024)
Xiaohan Chen, Jialin Liu, Wotao Yin
Learning to optimize: A tutorial for continuous and mixed-integer optimization. CoRR (2024)
Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai
Towards Constituting Mathematical Structures for Learning to Optimize. ICML (2023)
Mou Sun, Tao Li, Wotao Yin
MindOpt Adapter for CPLEX Benchmarking Performance Analysis. CoRR (2023)
Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai
Towards Constituting Mathematical Structures for Learning to Optimize. CoRR (2023)
Qi Qi, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
Attentional-Biased Stochastic Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023)
Yutong He, Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression. CoRR (2023)
Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin
On Representing Linear Programs by Graph Neural Networks. ICLR (2023)
Haoyu Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin
DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. CoRR (2023)
Quan Xiao, Han Shen, Wotao Yin, Tianyi Chen
Alternating Projected SGD for Equality-constrained Bilevel Optimization. AISTATS (2023)
Ziang Chen, Jianfeng Lu, Huajie Qian, Xinshang Wang, Wotao Yin
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent. AISTATS (2023)
Mengyuan Zhang, Wotao Yin, Mengchang Wang, Yangbin Shen, Peng Xiang, You Wu, Liang Zhao, Junqiu Pan, Hu Jiang, KuoLing Huang
MindOpt Tuner: Boost the Performance of Numerical Software by Automatic Parameter Tuning. CoRR (2023)
Ming Jin, Bilgehan Sel, Fnu Hardeep, Wotao Yin
A Human-on-the-Loop Optimization Autoformalism Approach for Sustainability. CoRR (2023)
Lisang Ding, Kexin Jin, Bicheng Ying, Kun Yuan, Wotao Yin
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm. ICML (2023)
Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin
On Representing Mixed-Integer Linear Programs by Graph Neural Networks. ICLR (2023)
Lisang Ding, Kexin Jin, Bicheng Ying, Kun Yuan, Wotao Yin
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm. CoRR (2023)
Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin
Safeguarded Learned Convex Optimization. AAAI (2023)
Tianyi Chen, Yuejiao Sun, Quan Xiao, Wotao Yin
A Single-Timescale Method for Stochastic Bilevel Optimization. AISTATS (2022)
Haixiang Zhang, Andre Milzarek, Zaiwen Wen, Wotao Yin
On the geometric analysis of a quartic-quadratic optimization problem under a spherical constraint. Math. Program. 195 (1) (2022)
Yiyang Liu, Zaiwen Wen, Wotao Yin
A Multiscale Semi-Smooth Newton Method for Optimal Transport. J. Sci. Comput. 91 (2) (2022)
Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression. CoRR (2022)
Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan
Communication-Efficient Topologies for Decentralized Learning with O(1) Consensus Rate. CoRR (2022)
Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan
Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate. NeurIPS (2022)
Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods. CoRR (2022)
Lisang Ding, Wuchen Li, Stanley J. Osher, Wotao Yin
A Mean Field Game Inverse Problem. J. Sci. Comput. 92 (1) (2022)
Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin
On Representing Linear Programs by Graph Neural Networks. CoRR (2022)
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 (2022)
HanQin Cai, Daniel McKenzie, Wotao Yin, Zhenliang Zhang
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling. SIAM J. Optim. 32 (2) (2022)
Quan Xiao, Han Shen, Wotao Yin, Tianyi Chen
Alternating Implicit Projected SGD and Its Efficient Variants for Equality-constrained Bilevel Optimization. CoRR (2022)
Howard Heaton, Samy Wu Fung, Alex Tong Lin, Stanley J. Osher, Wotao Yin
Wasserstein-Based Projections with Applications to Inverse Problems. SIAM J. Math. Data Sci. 4 (2) (2022)
Jinshan Zeng, Wotao Yin, Ding-Xuan Zhou
Moreau Envelope Augmented Lagrangian Method for Nonconvex Optimization with Linear Constraints. J. Sci. Comput. 91 (2) (2022)
Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. CoRR (2022)
Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression. NeurIPS (2022)
Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin
On Representing Mixed-Integer Linear Programs by Graph Neural Networks. CoRR (2022)
Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. NeurIPS (2022)
Samy Wu Fung, Howard Heaton, Qiuwei Li, Daniel McKenzie, Stanley J. Osher, Wotao Yin
JFB: Jacobian-Free Backpropagation for Implicit Networks. AAAI (2022)
Ernest K. Ryu, Robert Hannah, Wotao Yin
Scaled relative graphs: nonexpansive operators via 2D Euclidean geometry. Math. Program. 194 (1) (2022)
Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang
Learning A Minimax Optimizer: A Pilot Study. ICLR (2021)
Tianyi Chen, Yuejiao Sun, Wotao Yin
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization. IEEE Trans. Signal Process. 69 (2021)
Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
Accelerating Gossip SGD with Periodic Global Averaging. CoRR (2021)
Yanli Liu, Yuejiao Sun, Wotao Yin
Decentralized Learning With Lazy and Approximate Dual Gradients. IEEE Trans. Signal Process. 69 (2021)
HanQin Cai, Yuchen Lou, Daniel McKenzie, Wotao Yin
A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization. CoRR (2021)
Samy Wu Fung, Howard Heaton, Qiuwei Li, Daniel McKenzie, Stanley J. Osher, Wotao Yin
Fixed Point Networks: Implicit Depth Models with Jacobian-Free Backprop. CoRR (2021)
Fei Feng, Wotao Yin, Alekh Agarwal, Lin F. Yang
Provably Correct Optimization and Exploration with Non-linear Policies. CoRR (2021)
Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
A Novel Convergence Analysis for Algorithms of the Adam Family. CoRR (2021)
Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders. NeurIPS (2021)
Tianyi Chen, Ziye Guo, Yuejiao Sun, Wotao Yin
CADA: Communication-Adaptive Distributed Adam. AISTATS (2021)
Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin
Hyperparameter Tuning is All You Need for LISTA. CoRR (2021)
Yanli Liu, Yunbei Xu, Wotao Yin
Acceleration of Primal-Dual Methods by Preconditioning and Simple Subproblem Procedures. J. Sci. Comput. 86 (2) (2021)
Tianyi Chen, Yuejiao Sun, Wotao Yin
Communication-Adaptive Stochastic Gradient Methods for Distributed Learning. IEEE Trans. Signal Process. 69 (2021)
Tianyi Chen, Yuejiao Sun, Wotao Yin
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems. NeurIPS (2021)
Bicheng Ying, Kun Yuan, Hanbin Hu, Yiming Chen, Wotao Yin
BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning. CoRR (2021)
Yuejiao Sun, Tianyi Chen, Wotao Yin
An Optimal Stochastic Compositional Optimization Method with Applications to Meta Learning. ICASSP (2021)
Tianyi Chen, Yuejiao Sun, Wotao Yin
A Single-Timescale Stochastic Bilevel Optimization Method. CoRR (2021)
Howard Heaton, Samy Wu Fung, Aviv Gibali, Wotao Yin
Feasibility-based Fixed Point Networks. CoRR (2021)
Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Wotao Yin, Yang Liu
FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data. IEEE Trans. Signal Process. 69 (2021)
HanQin Cai, Yuchen Lou, Daniel McKenzie, Wotao Yin
A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization. ICML (2021)
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Provably Correct Optimization and Exploration with Non-linear Policies. ICML (2021)
Bum-Su Kim, HanQin Cai, Daniel McKenzie, Wotao Yin
Curvature-Aware Derivative-Free Optimization. CoRR (2021)
Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin
Exponential Graph is Provably Efficient for Decentralized Deep Training. NeurIPS (2021)
Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin
Learning to Optimize: A Primer and A Benchmark. CoRR (2021)
Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training. ICCV (2021)
Tianyi Chen, Yuejiao Sun, Wotao Yin
Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems. CoRR (2021)
Jialin Liu, Wotao Yin, Wuchen Li, Yat Tin Chow
Multilevel Optimal Transport: A Fast Approximation of Wasserstein-1 Distances. SIAM J. Sci. Comput. 43 (1) (2021)
Miao Xie, Wotao Yin, Huan Xu
AutoBandit: A Meta Bandit Online Learning System. IJCAI (2021)
Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin
Hyperparameter Tuning is All You Need for LISTA. NeurIPS (2021)
Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin
Exponential Graph is Provably Efficient for Decentralized Deep Training. CoRR (2021)
HanQin Cai, Jialin Liu, Wotao Yin
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. NeurIPS (2021)
Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
Accelerating Gossip SGD with Periodic Global Averaging. ICML (2021)
HanQin Cai, Jialin Liu, Wotao Yin
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. CoRR (2021)
Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training. CoRR (2021)
Howard Heaton, Daniel McKenzie, Qiuwei Li, Samy Wu Fung, Stanley J. Osher, Wotao Yin
Learn to Predict Equilibria via Fixed Point Networks. CoRR (2021)
Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
On Stochastic Moving-Average Estimators for Non-Convex Optimization. CoRR (2021)
Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin
On the Comparison between Cyclic Sampling and Random Reshuffling. CoRR (2021)
Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen
Hybrid Federated Learning: Algorithms and Implementation. CoRR (2020)
Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning. NeurIPS (2020)
Tianyi Chen, Ziye Guo, Yuejiao Sun, Wotao Yin
CADA: Communication-Adaptive Distributed Adam. CoRR (2020)
Tianyi Chen, Yuejiao Sun, Wotao Yin
LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning. CoRR (2020)
Chun-Na Li, Yuan-Hai Shao, Wotao Yin, Ming-Zeng Liu
Robust and Sparse Linear Discriminant Analysis via an Alternating Direction Method of Multipliers. IEEE Trans. Neural Networks Learn. Syst. 31 (3) (2020)
Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin
Safeguarded Learned Convex Optimization. CoRR (2020)
Yanli Liu, Yuan Gao, Wotao Yin
An Improved Analysis of Stochastic Gradient Descent with Momentum. NeurIPS (2020)
Howard Heaton, Samy Wu Fung, Alex Tong Lin, Stanley J. Osher, Wotao Yin
Projecting to Manifolds via Unsupervised Learning. CoRR (2020)
Tao Sun, Yuejiao Sun, Yangyang Xu, Wotao Yin
Markov chain block coordinate descent. Comput. Optim. Appl. 75 (1) (2020)
Huan Li, Cong Fang, Wotao Yin, Zhouchen Lin
Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters. IEEE Trans. Signal Process. 68 (2020)
Xianghui Mao, Kun Yuan, Yubin Hu, Yuantao Gu, Ali H. Sayed, Wotao Yin
Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization. IEEE Trans. Signal Process. 68 (2020)
Xinmeng Huang, Ernest K. Ryu, Wotao Yin
Scaled Relative Graph of Normal Matrices. CoRR (2020)
Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods. NeurIPS (2020)
HanQin Cai, Daniel McKenzie, Wotao Yin, Zhenliang Zhang
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling. CoRR (2020)
Tianyi Chen, Xiao Jin, Yuejiao Sun, Wotao Yin
VAFL: a Method of Vertical Asynchronous Federated Learning. CoRR (2020)
Tianyi Chen, Yuejiao Sun, Wotao Yin
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization. CoRR (2020)
Yibo Zeng, Fei Feng, Wotao Yin
AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity. AISTATS (2020)
Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang
Provably Efficient Exploration for RL with Unsupervised Learning. CoRR (2020)

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Publication Activity (10 Years)

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Wotao Yin