Jin, Yujia

16 publications

ICML 2025 Catoni Contextual Bandits Are Robust to Heavy-Tailed Rewards Chenlu Ye, Yujia Jin, Alekh Agarwal, Tong Zhang

COLT 2024 Faster Spectral Density Estimation and Sparsification in the Nuclear Norm (Extended Abstract) Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh

NeurIPS 2024 Truncated Variance Reduced Value Iteration Yujia Jin, Ishani Karmarkar, Aaron Sidford, Jiayi Wang

COLT 2023 Moments, Random Walks, and Limits for Spectrum Approximation Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh

ICML 2023 Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling Adam Bouland, Yosheb M Getachew, Yujia Jin, Aaron Sidford, Kevin Tian

COLT 2023 VO$Q$L: Towards Optimal Regret in Model-Free RL with Nonlinear Function Approximation Alekh Agarwal, Yujia Jin, Tong Zhang

NeurIPS 2022 Optimal and Adaptive Monteiro-Svaiter Acceleration Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin, Aaron Sidford

ICML 2022 RECAPP: Crafting a More Efficient Catalyst for Convex Optimization Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford

COLT 2022 Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods Yujia Jin, Aaron Sidford, Kevin Tian

NeurIPS 2021 Stochastic Bias-Reduced Gradient Methods Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford

COLT 2021 Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford

ICML 2021 Towards Tight Bounds on the Sample Complexity of Average-Reward MDPs Yujia Jin, Aaron Sidford

NeurIPS 2020 Acceleration with a Ball Optimization Oracle Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian

ICML 2020 Efficiently Solving MDPs with Stochastic Mirror Descent Yujia Jin, Aaron Sidford

NeurIPS 2019 Principal Component Projection and Regression in Nearly Linear Time Through Asymmetric SVRG Yujia Jin, Aaron Sidford

NeurIPS 2019 Variance Reduction for Matrix Games Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian