Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise. - Xuanqing Liu; Tesi Xiao; Si Si; Qin Cao; Sanjiv Kumar; Cho-Jui Hsieh (CoRR, 2019)

How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework. - Xuanqing Liu; Tesi Xiao; Si Si; Qin Cao; Sanjiv Kumar; Cho-Jui Hsieh (CVPR, 2020)

Statistical Inference for Polyak-Ruppert Averaged Zeroth-order Stochastic Gradient Algorithm. - Yanhao Jin; Tesi Xiao; Krishnakumar Balasubramanian 002 (CoRR, 2021)

Field-wise Embedding Size Search via Structural Hard Auxiliary Mask Pruning for Click-Through Rate Prediction. - Tesi Xiao; Xia Xiao; Ming Chen; Youlong Chen (DL4SR@CIKM, 2022)

A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization. - Tesi Xiao; Krishnakumar Balasubramanian 002; Saeed Ghadimi (NeurIPS, 2022)

Improved complexities for stochastic conditional gradient methods under interpolation-like conditions. - Tesi Xiao; Krishnakumar Balasubramanian 002; Saeed Ghadimi (Oper. Res. Lett., 2022)

Towards Sequential Counterfactual Learning to Rank. - Tesi Xiao; Branislav Kveton; Sumeet Katariya; Tanmay Gangwani; Anshuka Rangi (SIGIR-AP, 2023)

A one-sample decentralized proximal algorithm for non-convex stochastic composite optimization. - Tesi Xiao; Xuxing Chen; Krishnakumar Balasubramanian 002; Saeed Ghadimi (UAI, 2023)

Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow. - Yinuo Ren; Tesi Xiao; Tanmay Gangwani; Anshuka Rangi; Holakou Rahmanian; Lexing Ying; Subhajit Sanyal (AISTATS, 2024)

Accelerating Sinkhorn algorithm with sparse Newton iterations. - Xun Tang; Michael Shavlovsky; Holakou Rahmanian; Elisa Tardini; Kiran Koshy Thekumparampil; Tesi Xiao; Lexing Ying (ICLR, 2024)

A Sinkhorn-type Algorithm for Constrained Optimal Transport. - Xun Tang; Holakou Rahmanian; Michael Shavlovsky; Kiran Koshy Thekumparampil; Tesi Xiao; Lexing Ying (CoRR, 2024)

HyperDPO: Hypernetwork-based Multi-Objective Fine-Tuning Framework. - Yinuo Ren; Tesi Xiao; Michael Shavlovsky; Lexing Ying; Holakou Rahmanian (CoRR, 2024)

Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions. - Xuxing Chen; Tesi Xiao; Krishnakumar Balasubramanian 002 (J. Mach. Learn. Res., 2024)

Orbit: A Framework for Designing and Evaluating Multi-objective Rankers. - Chenyang Yang 002; Tesi Xiao; Michael Shavlovsky; Christian Kästner; Tongshuang Wu (IUI, 2025)

COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework. - Yinuo Ren; Tesi Xiao; Michael Shavlovsky; Lexing Ying; Holakou Rahmanian (UAI, 2025)

RewardRank: Optimizing True Learning-to-Rank Utility. - Gaurav Bhatt; Kiran Koshy Thekumparampil; Tanmay Gangwani; Tesi Xiao; Leonid Sigal (CoRR, 2025)

An efficient algorithm for entropic optimal transport under martingale-type constraints. - Xun Tang; Michael Shavlovsky; Holakou Rahmanian; Tesi Xiao; Lexing Ying (CoRR, 2025)