Research

Research Interests

My current interests include

• Optimization and Game Theory.

• Machine Learning.

• Optimal Transport.

• Large-Scale Text Analytics.

Preprints

• Perseus: A Simple and Optimal High-Order Method for Variational Inequalities

  • Tianyi Lin and Michael I. Jordan

• A Nonasymptotic Analysis of Gradient Descent Ascent for Nonconvex-Concave Minimax Problems

  • Tianyi Lin, Chi Jin and Michael I. Jordan

• Adaptive, Doubly Optimal No-Regret Learning in Games with Gradient Feedback

  • (α-β order) Michael I. Jordan, Tianyi Lin and Zhengyuan Zhou

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

  • Tianyi Lin, Panayotis Mertikopoulos and Michael. I. Jordan

• Deterministic Nonsmooth Nonconvex Optimization (An earlier version is available here: link)

  • (α-β order) Michael I. Jordan, Guy Kornowski, Tianyi Lin, Ohad Shamir and Manolis Zampetakis

• A Continuous-Time Perspective on Optimal Methods for Monotone Equation Problems

  • Tianyi Lin and Michael I. Jordan

• Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback

  • Tianyi Lin, Zhengyuan Zhou, Wenjia Ba and Jiawei Zhang

Selected Refereed Journal Publications

• Monotone Inclusions, Acceleration and Closed-Loop Control

  • Tianyi Lin and Michael I. Jordan

  • Mathematics of Operations Research. Forthcoming. 2023

• A Control-Theoretic Perspective on Optimal High-Order Optimization

  • Tianyi Lin and Michael I. Jordan

  • Mathematical Programming (Series A). 195 (1): 929-975. 2022

• On the Efficiency of Entropic Regularized Algorithms for Optimal Transport

  • Tianyi Lin, Nhat Ho and Michael I. Jordan

  • Journal of Machine Learning Research. 23 (137): 1-42. 2022

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

  • (α-β order) Bo Jiang, Tianyi Lin and Shuzhong Zhang

  • SIAM Journal on Optimization. 30 (4): 2897-2926. 2020

• On the Global Linear Convergence of the ADMM with Multi-Block Variables

  • Tianyi Lin, Shiqian Ma and Shuzhong Zhang

  • SIAM Journal on Optimization. 25 (3): 1478-1497. 2015

Selected Refereed Conference Proceedings

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

  • Tianyi Lin, Zeyu Zheng and Michael I. Jordan

  • Neural Information Processing Systems (NeurIPS’2022)

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

  • (α-β order) Michael I. Jordan, Tianyi Lin and Emmanouil-Vasileios Vlatakis-Gkaragkounis

  • (Oral) Neural Information Processing Systems (NeurIPS’2022)

• Projection Robust Wasserstein Distance and Riemannian Optimization

  • Tianyi Lin*, Chenyou Fan*, Nhat Ho, Macro Cuturi and Michael I. Jordan

  • (Spotlight) Neural Information Processing Systems (NeurIPS’2020)

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

  • Tianyi Lin, Nhat Ho, Xi Chen, Macro Cuturi and Michael I. Jordan

  • Neural Information Processing Systems (NeurIPS’2020)

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

  • Tianyi Lin*, Zhengyuan Zhou*, Panayotis Mertikopoulos and Michael I. Jordan

  • International Conference on Machine Learning (ICML’2020)

• On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems

  • Tianyi Lin, Chi Jin and Michael I. Jordan

  • International Conference on Machine Learning (ICML’2020)

• Near-Optimal Algorithms for Minimax Optimization

  • Tianyi Lin, Chi Jin and Michael I. Jordan

  • Conference on Learning Theory (COLT’2020)

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

  • Tianyi Lin*, Nhat Ho* and Michael I. Jordan

  • International Conference on Machine Learning (ICML’2019)

• The Dual-Sparse Topic Model: Mining Focused Topics and Focused Terms in Short Text

  • Tianyi Lin*, Wentao Tian*, Qiaozhu Mei and Hong Cheng

  • International World Wide Web Conference (WWW’2014)