First-Order Open-Universe POMDPs. - Siddharth Srivastava 001; Stuart Russell 001; Paul Ruan; Xiang Cheng 006 (UAI, 2014)

Asymptotic behavior of ℓp-based Laplacian regularization in semi-supervised learning. - Ahmed El Alaoui; Xiang Cheng 006; Aaditya Ramdas; Martin J. Wainwright; Michael I. Jordan (CoRR, 2016)

FLAG: Fast Linearly-Coupled Adaptive Gradient Method. - Xiang Cheng 006; Farbod Roosta-Khorasani; Peter L. Bartlett; Michael W. Mahoney (CoRR, 2016)

FLAG n' FLARE: Fast Linearly-Coupled Adaptive Gradient Methods. - Xiang Cheng 006; Fred (Farbod) Roosta; Stefan Palombo; Peter L. Bartlett; Michael W. Mahoney (AISTATS, 2018)

Convergence of Langevin MCMC in KL-divergence. - Xiang Cheng 006; Peter L. Bartlett (ALT, 2018)

Underdamped Langevin MCMC: A non-asymptotic analysis. - Xiang Cheng 006; Niladri S. Chatterji; Peter L. Bartlett; Michael I. Jordan (COLT, 2018)

Sharp Convergence Rates for Langevin Dynamics in the Nonconvex Setting. - Xiang Cheng 006; Niladri S. Chatterji; Yasin Abbasi-Yadkori; Peter L. Bartlett; Michael I. Jordan (CoRR, 2018)

Quantitative Central Limit Theorems for Discrete Stochastic Processes. - Xiang Cheng 006; Peter L. Bartlett; Michael I. Jordan (CoRR, 2019)

Is There an Analog of Nesterov Acceleration for MCMC? - Yi-An Ma; Niladri S. Chatterji; Xiang Cheng 006; Nicolas Flammarion; Peter L. Bartlett; Michael I. Jordan (CoRR, 2019)

Quantitative W1 Convergence of Langevin-Like Stochastic Processes with Non-Convex Potential State-Dependent Noise. - Xiang Cheng 006; Dong Yin; Peter L. Bartlett; Michael I. Jordan (CoRR, 2019)

Variational perspective on local graph clustering. - Kimon Fountoulakis; Farbod Roosta-Khorasani; Julian Shun; Xiang Cheng 006; Michael W. Mahoney (Math. Program., 2019)

Stochastic Gradient and Langevin Processes. - Xiang Cheng 006; Dong Yin; Peter L. Bartlett; Michael I. Jordan (ICML, 2020)