Tianyi Lin

According to our database, Tianyi Lin authored at least 54 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems.

Michael I. Jordan, Tianyi Lin, Manolis Zampetakis

J. Mach. Learn. Res., 2023

A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport.

Tianyi Lin, Marco Cuturi, Michael I. Jordan

CoRR, 2023

Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback.

Michael I. Jordan, Tianyi Lin, Zhengyuan Zhou

CoRR, 2023

Curvature-Independent Last-Iterate Convergence for Games on Riemannian Manifolds.

Yang Cai, Michael I. Jordan, Tianyi Lin, Argyris Oikonomou, Emmanouil V. Vlatakis-Gkaragkounis

CoRR, 2023

PPO-Based Energy-Efficient Power Control and Spectrum Allocation in In-Vehicle HetNets.

Tianyi Lin, Jun Du, Haijun Zhang, Arumugam Nallanathan, Jun Wang

Proceedings of the IEEE Global Communications Conference, 2023

Deterministic Nonsmooth Nonconvex Optimization.

Michael I. Jordan, Guy Kornowski, Tianyi Lin, Ohad Shamir, Manolis Zampetakis

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

A control-theoretic perspective on optimal high-order optimization.

Tianyi Lin, Michael I. Jordan

Math. Program., 2022

On the Efficiency of Entropic Regularized Algorithms for Optimal Transport.

Tianyi Lin, Nhat Ho, Michael I. Jordan

J. Mach. Learn. Res., 2022

On the Complexity of Approximating Multimarginal Optimal Transport.

Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan

J. Mach. Learn. Res., 2022

Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling.

Xi Chen, Bo Jiang, Tianyi Lin, Shuzhong Zhang

J. Mach. Learn. Res., 2022

Explicit Second-Order Min-Max Optimization Methods with Optimal Convergence Guarantee.

Tianyi Lin, Panayotis Mertikopoulos, Michael I. Jordan

CoRR, 2022

On the Complexity of Deterministic Nonsmooth and Nonconvex Optimization.

Michael I. Jordan, Tianyi Lin, Manolis Zampetakis

CoRR, 2022

Understanding Performance of Long-Document Ranking Models through Comprehensive Evaluation and Leaderboarding.

Leonid Boytsov, Tianyi Lin, Fangwei Gao, Yutian Zhao, Jeffrey Huang, Eric Nyberg

CoRR, 2022

A Continuous-Time Perspective on Monotone Equation Problems.

Tianyi Lin, Michael I. Jordan

CoRR, 2022

Perseus: A Simple High-Order Regularization Method for Variational Inequalities.

Tianyi Lin, Michael I. Jordan

CoRR, 2022

Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization.

Tianyi Lin, Zeyu Zheng, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces.

Michael I. Jordan, Tianyi Lin, Emmanouil V. Vlatakis-Gkaragkounis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback.

Tianyi Lin, Aldo Pacchiano, Yaodong Yu, Michael I. Jordan

Proceedings of the International Conference on Machine Learning, 2022

Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization.

Yaodong Yu, Tianyi Lin, Eric V. Mazumdar, Michael I. Jordan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms.

Nhat Ho, Tianyi Lin, Michael I. Jordan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

An ADMM-based interior-point method for large-scale linear programming.

Tianyi Lin, Shiqian Ma, Yinyu Ye, Shuzhong Zhang

Optim. Methods Softw., 2021

Optimal No-Regret Learning in Strongly Monotone Games with Bandit Feedback.

Tianyi Lin, Zhengyuan Zhou, Wenjia Ba, Jiawei Zhang

CoRR, 2021

On Monotone Inclusions, Acceleration and Closed-Loop Control.

Tianyi Lin, Michael I. Jordan

CoRR, 2021

Relaxed Wasserstein with Applications to GANs.

Xin Guo, Johnny Hong, Tianyi Lin, Nan Yang

Proceedings of the IEEE International Conference on Acoustics, 2021

A Variational Inequality Approach to Bayesian Regression Games.

Wenshuo Guo, Michael I. Jordan, Tianyi Lin

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification.

Tianyi Lin, Zeyu Zheng, Elynn Y. Chen, Marco Cuturi, Michael I. Jordan

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

A Unified Adaptive Tensor Approximation Scheme to Accelerate Composite Convex Optimization.

Bo Jiang, Tianyi Lin, Shuzhong Zhang

SIAM J. Optim., 2020

Revisiting Fixed Support Wasserstein Barycenter: Computational Hardness and Efficient Algorithms.

Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan

CoRR, 2020

Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm.

Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Projection Robust Wasserstein Distance and Riemannian Optimization.

Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games.

Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan

Proceedings of the 37th International Conference on Machine Learning, 2020

On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems.

Tianyi Lin, Chi Jin, Michael I. Jordan

Proceedings of the 37th International Conference on Machine Learning, 2020

Near-Optimal Algorithms for Minimax Optimization.

Tianyi Lin, Chi Jin, Michael I. Jordan

Proceedings of the Conference on Learning Theory, 2020

New Proximal Newton-Type Methods for Convex Optimization.

Ilan Adler, Zhiyue Tom Hu, Tianyi Lin

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient.

Tianyi Lin, Chengyou Fan, Mengdi Wang, Michael I. Jordan

Proceedings of the 2020 American Control Conference, 2020

2019

On the Acceleration of the Sinkhorn and Greenkhorn Algorithms for Optimal Transport.

Tianyi Lin, Nhat Ho, Michael I. Jordan

CoRR, 2019

Global Error Bounds and Linear Convergence for Gradient-Based Algorithms for Trend Filtering and 𝓁₁-Convex Clustering.

Nhat Ho, Tianyi Lin, Michael I. Jordan

CoRR, 2019

Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis.

Bo Jiang, Tianyi Lin, Shiqian Ma, Shuzhong Zhang

Comput. Optim. Appl., 2019

Sparsemax and Relaxed Wasserstein for Topic Sparsity.

Tianyi Lin, Zhiyue Hu, Xin Guo

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms.

Tianyi Lin, Nhat Ho, Michael I. Jordan

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Distributed Linearized Alternating Direction Method of Multipliers for Composite Convex Consensus Optimization.

Necdet Serhat Aybat, Zi Wang, Tianyi Lin, Shiqian Ma

IEEE Trans. Autom. Control., 2018

Global Convergence of Unmodified 3-Block ADMM for a Class of Convex Minimization Problems.

Tianyi Lin, Shiqian Ma, Shuzhong Zhang

J. Sci. Comput., 2018

On the iteration complexity analysis of Stochastic Primal-Dual Hybrid Gradient approach with high probability.

Linbo Qiao, Tianyi Lin, Qi Qin, Xicheng Lu

Neurocomputing, 2018

Stochastic Primal-Dual Proximal ExtraGradient descent for compositely regularized optimization.

Tianyi Lin, Linbo Qiao, Teng Zhang, Jiashi Feng, Bofeng Zhang

Neurocomputing, 2018

Improved Oracle Complexity for Stochastic Compositional Variance Reduced Gradient.

Tianyi Lin, Chenyou Fan, Mengdi Wang, Michael I. Jordan

CoRR, 2018

2017

Exploiting interactions of review text, hidden user communities and item groups, and time for collaborative filtering.

Yinqing Xu, Qian Yu, Wai Lam, Tianyi Lin

Knowl. Inf. Syst., 2017

An Extragradient-Based Alternating Direction Method for Convex Minimization.

Tianyi Lin, Shiqian Ma, Shuzhong Zhang

Found. Comput. Math., 2017

2016

Iteration Complexity Analysis of Multi-block ADMM for a Family of Convex Minimization Without Strong Convexity.

Tianyi Lin, Shiqian Ma, Shuzhong Zhang

J. Sci. Comput., 2016

On Stochastic Primal-Dual Hybrid Gradient Approach for Compositely Regularized Minimization.

Linbo Qiao, Tianyi Lin, Yu-Gang Jiang, Fan Yang, Wei Liu, Xicheng Lu

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Understanding Sparse Topical Structure of Short Text via Stochastic Variational-Gibbs Inference.

Tianyi Lin, Siyuan Zhang, Hong Cheng

Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015

On the Global Linear Convergence of the ADMM with MultiBlock Variables.

Tianyi Lin, Shiqian Ma, Shuzhong Zhang

SIAM J. Optim., 2015

2014

The dual-sparse topic model: mining focused topics and focused terms in short text.

Tianyi Lin, Wentao Tian, Qiaozhu Mei, Hong Cheng

Proceedings of the 23rd International World Wide Web Conference, 2014

Latent Aspect Mining via Exploring Sparsity and Intrinsic Information.

Yinqing Xu, Tianyi Lin, Wai Lam, Zirui Zhou, Hong Cheng, Anthony Man-Cho So

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Collaborative Filtering Incorporating Review Text and Co-clusters of Hidden User Communities and Item Groups.

Yinqing Xu, Wai Lam, Tianyi Lin

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014