Kwon, Jeongyeol

20 publications

ICML 2025 A Classification View on Meta Learning Bandits Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar

COLT 2025 Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing J. Jon Ryu, Jeongyeol Kwon, Benjamin Koppe, Kwang-Sung Jun

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

AISTATS 2025 Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way Jeongyeol Kwon, Luke Dotson, Yudong Chen, Qiaomin Xie

ICLR 2024 On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert D Nowak

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

JMLR 2024 On the Computational and Statistical Complexity of Over-Parameterized Matrix Sensing Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis

ICML 2024 Prospective Side Information for Latent MDPs Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis

NeurIPS 2024 RL in Latent MDPs Is Tractable: Online Guarantees via Off-Policy Evaluation Jeongyeol Kwon, Shie Mannor, Constantine Caramanis, Yonathan Efroni

ICML 2023 A Fully First-Order Method for Stochastic Bilevel Optimization Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert D Nowak

ICML 2023 Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert D Nowak, Yixuan Li

ICML 2023 Reward-Mixing MDPs with Few Latent Contexts Are Learnable Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

ICML 2022 Coordinated Attacks Against Contextual Bandits: Fundamental Limits and Defense Mechanisms Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPS 2022 Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

AISTATS 2021 On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression Jeongyeol Kwon, Nhat Ho, Constantine Caramanis

NeurIPS 2021 RL for Latent MDPs: Regret Guarantees and a Lower Bound Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPS 2021 Reinforcement Learning in Reward-Mixing MDPs Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

AISTATS 2020 EM Converges for a Mixture of Many Linear Regressions Jeongyeol Kwon, Constantine Caramanis

COLT 2020 The EM Algorithm Gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians Jeongyeol Kwon, Constantine Caramanis

COLT 2019 Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression Jeongyeol Kwon, Wei Qian, Constantine Caramanis, Yudong Chen, Damek Davis