Label optimal regret bounds for online local learning. - Pranjal Awasthi; Moses Charikar; Kevin A. Lai; Andrej Risteski (COLT, 2015)

Agnostic Estimation of Mean and Covariance. - Kevin A. Lai; Anup B. Rao; Santosh S. Vempala (FOCS, 2016)

Amortized rotation cost in AVL trees. - Mahdi Amani; Kevin A. Lai; Robert E. Tarjan (Inf. Process. Lett., 2016)

$ ell_1$ Regression using Lewis Weights Preconditioning. - David Durfee; Kevin A. Lai; Saurabh Sawlani (CoRR, 2017)

Faster Rates for Convex-Concave Games. - Jacob D. Abernethy; Kevin A. Lai; Kfir Y. Levy; Jun-Kun Wang (COLT, 2018)

$ ell_1$ Regression using Lewis Weights Preconditioning and Stochastic Gradient Descent. - David Durfee; Kevin A. Lai; Saurabh Sawlani (COLT, 2018)

Differential Privacy for Growing Databases. - Rachel Cummings; Sara Krehbiel; Kevin A. Lai; Uthaipon Tao Tantipongpipat (NeurIPS, 2018)

Last-iterate convergence rates for min-max optimization. - Jacob D. Abernethy; Kevin A. Lai; Andre Wibisono (CoRR, 2019)

Fictitious Play: Convergence, Smoothness, and Optimism. - Jacob D. Abernethy; Kevin A. Lai; Andre Wibisono (CoRR, 2019)

Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization. - Jacob D. Abernethy; Kevin A. Lai; Andre Wibisono (ALT, 2021)

Fast Convergence of Fictitious Play for Diagonal Payoff Matrices. - Jacob D. Abernethy; Kevin A. Lai; Andre Wibisono (SODA, 2021)

Higher-Order Methods for Convex-Concave Min-Max Optimization and Monotone Variational Inequalities. - Brian Bullins; Kevin A. Lai (SIAM J. Optim., 2022)