Lyu, Hanbaek

15 publications

ICML 2025 Linear Convergence of Sinkhorn’s Algorithm for Generalized Static Schrödinger Bridge Rahul Choudhary, Hanbaek Lyu

NeurIPS 2025 Offline Actor-Critic for Average Reward MDPs William Powell, Jeongyeol Kwon, Qiaomin Xie, Hanbaek Lyu

ICML 2025 Sample Complexity of Branch-Length Estimation by Maximum Likelihood David Clancy, Hanbaek Lyu, Sebastien Roch

NeurIPSW 2024 A Fast and Efficient Randomized Quasi-Newton Method Danny Duan, Hanbaek Lyu

ICML 2024 Convergence and Complexity Guarantee for Inexact First-Order Riemannian Optimization Algorithms Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu

ICML 2024 On the Complexity of First-Order Methods in Stochastic Bilevel Optimization Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu

ICML 2024 Stochastic Optimization with Arbitrary Recurrent Data Sampling William Powell, Hanbaek Lyu

JMLR 2024 Stochastic Regularized Majorization-Minimization with Weakly Convex and Multi-Convex Surrogates Hanbaek Lyu

ICML 2024 Supervised Matrix Factorization: Local Landscape Analysis and Applications Joowon Lee, Hanbaek Lyu, Weixin Yao

ICML 2023 Complexity of Block Coordinate Descent with Proximal Regularization and Applications to Wasserstein CP-Dictionary Learning Dohyun Kwon, Hanbaek Lyu

ICML 2023 Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data Ahmet Alacaoglu, Hanbaek Lyu

NeurIPS 2023 Exponentially Convergent Algorithms for Supervised Matrix Factorization Joowon Lee, Hanbaek Lyu, Weixin Yao

JMLR 2023 Sampling Random Graph Homomorphisms and Applications to Network Data Analysis Hanbaek Lyu, Facundo Memoli, David Sivakoff

JMLR 2022 Online Nonnegative CP-Dictionary Learning for Markovian Data Hanbaek Lyu, Christopher Strohmeier, Deanna Needell

JMLR 2020 Online Matrix Factorization for Markovian Data and Applications to Network Dictionary Learning Hanbaek Lyu, Deanna Needell, Laura Balzano