Tianyi Lin - RankMe

95 papers A* 11A 9B 1C 1Misc 1Journal 67Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model? CoRR Jingyi Zhang, Tianyi Lin, Huanjin Yao, Xiang Lan, Shunyu Liu, Jiaxing Huang
2026	J	`jnl`	Reward-free Alignment for Conflicting Objectives. CoRR Peter L. Chen, Xiaopeng Li, Xi Chen, Tianyi Lin
2026	J	`jnl`	Stepwise Guided Policy Optimization: Coloring Your Incorrect Reasoning in GRPO. Trans. Mach. Learn. Res. Peter Chen, Xiaopeng Li, Ziniu Li, Xi Chen, Tianyi Lin
2026	J	`jnl`	Voluntary Renewable Programs: Optimal Pricing and Revenue Allocation. CoRR Zhiyuan Fan, Tianyi Lin, Bolun Xu
2025	J	`jnl`	A Direct Second-Order Method for Solving Two-Player Zero-Sum Games. CoRR David Yang, Yuan Gao, Tianyi Lin, Christian Kroer
2025	J	`jnl`	Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback. Oper. Res. Michael I. Jordan, Tianyi Lin, Zhengyuan Zhou
2025	J	`jnl`	ComPO: Preference Alignment via Comparison Oracles. CoRR Peter Chen, Xi Chen, Wotao Yin, Tianyi Lin
2025	J	`jnl`	Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback. Oper. Res. Wenjia Ba, Tianyi Lin, Jiawei Zhang, Zhengyuan Zhou
2025	J	`jnl`	Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward. CoRR Peter Chen, Xiaopeng Li, Ziniu Li, Wotao Yin, Xi Chen, Tianyi Lin
2025	—	`conf`	OWC4DT: a 25 Gbps Plug-And-Play Self-Alignment Optical Wireless Communication System for Distributed Training in Data Center. ICC Tianyi Lin, Siyuan Wang, Hongming Zhang, Jian Song
2025	J	`jnl`	Perseus: a simple and optimal high-order method for variational inequalities. Math. Program. Tianyi Lin, Michael I. Jordan
2025	—	`conf`	Positional Bias in Long-Document Ranking: Impact, Assessment, and Mitigation. IJCNLP-AACL (long papers) Leonid Boytsov, David Akinpelu, Nipun Katyal, Tianyi Lin, Fangwei Gao, Yutian Zhao, Jeffrey Huang, Eric Nyberg
2025	J	`jnl`	SciTS: Scientific Time Series Understanding and Generation with LLMs. CoRR Wen Wu, Ziyang Zhang, Liwei Liu, Xuenan Xu, Junlin Liu, Ke Fan, Qitan Lv, Jimin Zhuang, Chen Zhang, Zheqi Yuan, Siyuan Hou, Tianyi Lin, Kai Chen, Bowen Zhou, Chao Zhang
2025	J	`jnl`	Spectral Policy Optimization: Coloring your Incorrect Reasoning in GRPO. CoRR Peter Chen, Xiaopeng Li, Ziniu Li, Xi Chen, Tianyi Lin
2025	J	`jnl`	Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization. J. Mach. Learn. Res. Tianyi Lin, Chi Jin, Michael I. Jordan
2024	A	`conf`	A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport. AISTATS Tianyi Lin, Marco Cuturi, Michael I. Jordan
2024	J	`jnl`	Distributed Foundation Models for Multi-Modal Learning in 6G Wireless Networks. IEEE Wirel. Commun. Jun Du, Tianyi Lin, Chunxiao Jiang, Qianqian Yang, Faouzi Bader, Zhu Han
2024	J	`jnl`	Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization. CoRR Tianyi Lin, Chi Jin, Michael I. Jordan
2023	J	`jnl`	A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport. CoRR Tianyi Lin, Marco Cuturi, Michael I. Jordan
2023	J	`jnl`	Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback. CoRR Michael I. Jordan, Tianyi Lin, Zhengyuan Zhou
2023	J	`jnl`	Curvature-Independent Last-Iterate Convergence for Games on Riemannian Manifolds. CoRR Yang Cai, Michael I. Jordan, Tianyi Lin, Argyris Oikonomou, Emmanouil V. Vlatakis-Gkaragkounis
2023	A*	`conf`	Deterministic Nonsmooth Nonconvex Optimization. COLT Michael I. Jordan, Guy Kornowski, Tianyi Lin, Ohad Shamir, Manolis Zampetakis
2023	J	`jnl`	Deterministic Nonsmooth Nonconvex Optimization. CoRR Michael I. Jordan, Guy Kornowski, Tianyi Lin, Ohad Shamir, Manolis Zampetakis
2023	J	`jnl`	First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems. J. Mach. Learn. Res. Michael I. Jordan, Tianyi Lin, Manolis Zampetakis
2023	J	`jnl`	Monotone Inclusions, Acceleration, and Closed-Loop Control. Math. Oper. Res. Tianyi Lin, Michael I. Jordan
2023	B	`conf`	PPO-Based Energy-Efficient Power Control and Spectrum Allocation in In-Vehicle HetNets. GLOBECOM Tianyi Lin, Jun Du, Haijun Zhang, Arumugam Nallanathan, Jun Wang
2023	—	`—`	Structure-Driven Algorithm Design in Optimization and Machine Learning Tianyi Lin
2022	J	`jnl`	A Continuous-Time Perspective on Monotone Equation Problems. CoRR Tianyi Lin, Michael I. Jordan
2022	J	`jnl`	A control-theoretic perspective on optimal high-order optimization. Math. Program. Tianyi Lin, Michael I. Jordan
2022	J	`jnl`	Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling. J. Mach. Learn. Res. Xi Chen, Bo Jiang, Tianyi Lin, Shuzhong Zhang
2022	J	`jnl`	Explicit Second-Order Min-Max Optimization Methods with Optimal Convergence Guarantee. CoRR Tianyi Lin, Panayotis Mertikopoulos, Michael I. Jordan
2022	A	`conf`	Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization. AISTATS Yaodong Yu, Tianyi Lin, Eric V. Mazumdar, Michael I. Jordan
2022	A*	`conf`	First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces. NeurIPS Michael I. Jordan, Tianyi Lin, Emmanouil V. Vlatakis-Gkaragkounis
2022	J	`jnl`	First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces. CoRR Michael I. Jordan, Tianyi Lin, Emmanouil V. Vlatakis-Gkaragkounis
2022	J	`jnl`	First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems. CoRR Michael I. Jordan, Tianyi Lin, Manolis Zampetakis
2022	A*	`conf`	Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization. NeurIPS Tianyi Lin, Zeyu Zheng, Michael I. Jordan
2022	J	`jnl`	Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization. CoRR Tianyi Lin, Zeyu Zheng, Michael I. Jordan
2022	A	`conf`	On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms. AISTATS Nhat Ho, Tianyi Lin, Michael I. Jordan
2022	J	`jnl`	On the Complexity of Approximating Multimarginal Optimal Transport. J. Mach. Learn. Res. Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan
2022	J	`jnl`	On the Complexity of Deterministic Nonsmooth and Nonconvex Optimization. CoRR Michael I. Jordan, Tianyi Lin, Manolis Zampetakis
2022	J	`jnl`	On the Efficiency of Entropic Regularized Algorithms for Optimal Transport. J. Mach. Learn. Res. Tianyi Lin, Nhat Ho, Michael I. Jordan
2022	A*	`conf`	Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback. ICML Tianyi Lin, Aldo Pacchiano, Yaodong Yu, Michael I. Jordan
2022	J	`jnl`	Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback. CoRR Tianyi Lin, Aldo Pacchiano, Yaodong Yu, Michael I. Jordan
2022	J	`jnl`	Perseus: A Simple High-Order Regularization Method for Variational Inequalities. CoRR Tianyi Lin, Michael I. Jordan
2022	J	`jnl`	Understanding Performance of Long-Document Ranking Models through Comprehensive Evaluation and Leaderboarding. CoRR Leonid Boytsov, Tianyi Lin, Fangwei Gao, Yutian Zhao, Jeffrey Huang, Eric Nyberg
2021	—	`conf`	A Variational Inequality Approach to Bayesian Regression Games. CDC Wenshuo Guo, Michael I. Jordan, Tianyi Lin
2021	J	`jnl`	A Variational Inequality Approach to Bayesian Regression Games. CoRR Wenshuo Guo, Michael I. Jordan, Tianyi Lin
2021	J	`jnl`	An ADMM-based interior-point method for large-scale linear programming. Optim. Methods Softw. Tianyi Lin, Shiqian Ma, Yinyu Ye, Shuzhong Zhang
2021	J	`jnl`	Fast Distributionally Robust Learning with Variance Reduced Min-Max Optimization. CoRR Yaodong Yu, Tianyi Lin, Eric Mazumdar, Michael I. Jordan
2021	J	`jnl`	On Monotone Inclusions, Acceleration and Closed-Loop Control. CoRR Tianyi Lin, Michael I. Jordan
2021	A	`conf`	On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification. AISTATS Tianyi Lin, Zeyu Zheng, Elynn Y. Chen, Marco Cuturi, Michael I. Jordan
2021	J	`jnl`	Optimal No-Regret Learning in Strongly Monotone Games with Bandit Feedback. CoRR Tianyi Lin, Zhengyuan Zhou, Wenjia Ba, Jiawei Zhang
2021	Misc	`conf`	Relaxed Wasserstein with Applications to GANs. ICASSP Xin Guo, Johnny Hong, Tianyi Lin, Nan Yang
2020	J	`jnl`	A Unified Adaptive Tensor Approximation Scheme to Accelerate Composite Convex Optimization. SIAM J. Optim. Bo Jiang, Tianyi Lin, Shuzhong Zhang
2020	A*	`conf`	Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games. ICML Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan
2020	J	`jnl`	Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games. CoRR Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan
2020	A*	`conf`	Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm. NeurIPS Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan
2020	C	`conf`	Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient. ACC Tianyi Lin, Chengyou Fan, Mengdi Wang, Michael I. Jordan
2020	A*	`conf`	Near-Optimal Algorithms for Minimax Optimization. COLT Tianyi Lin, Chi Jin, Michael I. Jordan
2020	J	`jnl`	Near-Optimal Algorithms for Minimax Optimization. CoRR Tianyi Lin, Chi Jin, Michael I. Jordan
2020	—	`conf`	New Proximal Newton-Type Methods for Convex Optimization. CDC Ilan Adler, Zhiyue Tom Hu, Tianyi Lin
2020	A*	`conf`	On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems. ICML Tianyi Lin, Chi Jin, Michael I. Jordan
2020	J	`jnl`	On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification. CoRR Tianyi Lin, Zeyu Zheng, Elynn Y. Chen, Marco Cuturi, Michael I. Jordan
2020	A*	`conf`	Projection Robust Wasserstein Distance and Riemannian Optimization. NeurIPS Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan
2020	J	`jnl`	Projection Robust Wasserstein Distance and Riemannian Optimization. CoRR Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan
2020	J	`jnl`	Revisiting Fixed Support Wasserstein Barycenter: Computational Hardness and Efficient Algorithms. CoRR Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan
2019	J	`jnl`	A Control-Theoretic Perspective on Optimal High-Order Optimization. CoRR Tianyi Lin, Michael I. Jordan
2019	J	`jnl`	Global Error Bounds and Linear Convergence for Gradient-Based Algorithms for Trend Filtering and 𝓁 CoRR Nhat Ho, Tianyi Lin, Michael I. Jordan
2019	A*	`conf`	On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms. ICML Tianyi Lin, Nhat Ho, Michael I. Jordan
2019	J	`jnl`	On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms. CoRR Tianyi Lin, Nhat Ho, Michael I. Jordan
2019	J	`jnl`	On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems. CoRR Tianyi Lin, Chi Jin, Michael I. Jordan
2019	J	`jnl`	On the Acceleration of the Sinkhorn and Greenkhorn Algorithms for Optimal Transport. CoRR Tianyi Lin, Nhat Ho, Michael I. Jordan
2019	J	`jnl`	On the Complexity of Approximating Multimarginal Optimal Transport. CoRR Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan
2019	A	`conf`	Sparsemax and Relaxed Wasserstein for Topic Sparsity. WSDM Tianyi Lin, Zhiyue Hu, Xin Guo
2019	J	`jnl`	Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis. Comput. Optim. Appl. Bo Jiang, Tianyi Lin, Shiqian Ma, Shuzhong Zhang
2018	J	`jnl`	Distributed Linearized Alternating Direction Method of Multipliers for Composite Convex Consensus Optimization. IEEE Trans. Autom. Control. Necdet Serhat Aybat, Zi Wang, Tianyi Lin, Shiqian Ma
2018	J	`jnl`	Global Convergence of Unmodified 3-Block ADMM for a Class of Convex Minimization Problems. J. Sci. Comput. Tianyi Lin, Shiqian Ma, Shuzhong Zhang
2018	J	`jnl`	Improved Oracle Complexity for Stochastic Compositional Variance Reduced Gradient. CoRR Tianyi Lin, Chenyou Fan, Mengdi Wang, Michael I. Jordan
2018	J	`jnl`	On the Iteration Complexity Analysis of Stochastic Primal-Dual Hybrid Gradient Approach with High Probability. CoRR Linbo Qiao, Tianyi Lin, Qi Qin, Xicheng Lu
2018	J	`jnl`	On the iteration complexity analysis of Stochastic Primal-Dual Hybrid Gradient approach with high probability. Neurocomputing Linbo Qiao, Tianyi Lin, Qi Qin, Xicheng Lu
2018	J	`jnl`	Sparsemax and Relaxed Wasserstein for Topic Sparsity. CoRR Tianyi Lin, Zhiyue Hu, Xin Guo
2018	J	`jnl`	Stochastic Primal-Dual Proximal ExtraGradient descent for compositely regularized optimization. Neurocomputing Tianyi Lin, Linbo Qiao, Teng Zhang, Jiashi Feng, Bofeng Zhang
2017	J	`jnl`	An Extragradient-Based Alternating Direction Method for Convex Minimization. Found. Comput. Math. Tianyi Lin, Shiqian Ma, Shuzhong Zhang
2017	J	`jnl`	Exploiting interactions of review text, hidden user communities and item groups, and time for collaborative filtering. Knowl. Inf. Syst. Yinqing Xu, Qian Yu, Wai Lam, Tianyi Lin
2017	J	`jnl`	Relaxed Wasserstein with Applications to GANs. CoRR Xin Guo, Johnny Hong, Tianyi Lin, Nan Yang
2017	J	`jnl`	Stochastic Primal-Dual Proximal ExtraGradient descent for compositely regularized optimization. CoRR Tianyi Lin, Linbo Qiao, Teng Zhang, Jiashi Feng, Bofeng Zhang
2016	J	`jnl`	Iteration Complexity Analysis of Multi-block ADMM for a Family of Convex Minimization Without Strong Convexity. J. Sci. Comput. Tianyi Lin, Shiqian Ma, Shuzhong Zhang
2016	A	`conf`	On Stochastic Primal-Dual Hybrid Gradient Approach for Compositely Regularized Minimization. ECAI Linbo Qiao, Tianyi Lin, Yu-Gang Jiang, Fan Yang, Wei Liu, Xicheng Lu
2016	J	`jnl`	Structured Nonconvex and Nonsmooth Optimization: Algorithms and Iteration Complexity Analysis. CoRR Bo Jiang, Tianyi Lin, Shiqian Ma, Shuzhong Zhang
2016	A	`conf`	Understanding Sparse Topical Structure of Short Text via Stochastic Variational-Gibbs Inference. CIKM Tianyi Lin, Siyuan Zhang, Hong Cheng
2015	J	`jnl`	Global Convergence of Unmodified 3-Block ADMM for a Class of Convex Minimization Problems. CoRR Tianyi Lin, Shiqian Ma, Shuzhong Zhang
2015	J	`jnl`	On the Global Linear Convergence of the ADMM with MultiBlock Variables. SIAM J. Optim. Tianyi Lin, Shiqian Ma, Shuzhong Zhang
2014	A	`conf`	Collaborative Filtering Incorporating Review Text and Co-clusters of Hidden User Communities and Item Groups. CIKM Yinqing Xu, Wai Lam, Tianyi Lin
2014	A	`conf`	Latent Aspect Mining via Exploring Sparsity and Intrinsic Information. CIKM Yinqing Xu, Tianyi Lin, Wai Lam, Zirui Zhou, Hong Cheng, Anthony Man-Cho So
2014	A*	`conf`	The dual-sparse topic model: mining focused topics and focused terms in short text. WWW Tianyi Lin, Wentao Tian, Qiaozhu Mei, Hong Cheng