Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM. - Zhou Fan; Roy R. Lederman; Yi Sun 010; Tianhao Wang 017; Sheng Xu (CoRR, 2021)

What Happens after SGD Reaches Zero Loss? –A Mathematical Framework. - Zhiyuan Li 005; Tianhao Wang 017; Sanjeev Arora (ICLR, 2022)

Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent. - Zhiyuan Li 005; Tianhao Wang 017; Jason D. Lee; Sanjeev Arora (NeurIPS, 2022)

Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay. - Zhiyuan Li 005; Tianhao Wang 017; Dingli Yu (NeurIPS, 2022)

Universality of Approximate Message Passing algorithms and tensor networks. - Tianhao Wang 017; Xinyi Zhong; Zhou Fan (CoRR, 2022)

The Marginal Value of Momentum for Small Learning Rate SGD. - Runzhe Wang; Sadhika Malladi; Tianhao Wang 017; Kaifeng Lyu; Zhiyuan Li 005 (ICLR, 2024)

How Well Can Transformers Emulate In-Context Newton's Method? - Angeliki Giannou; Liu Yang 001; Tianhao Wang 017; Dimitris Papailiopoulos; Jason D. Lee (AISTATS, 2025)