Jeongyeol Kwon

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 29

Top Topics

Mixture Components

Policy Evaluation

Partially Observable

Top Venues

Publications

Jeongyeol Kwon, Liu Yang, Robert D. Nowak, Josiah Hanna
Future Prediction Can be a Strong Evidence of Good History Representation in Partially Observable Environments. CoRR (2024)
Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu
On the Complexity of First-Order Methods in Stochastic Bilevel Optimization. CoRR (2024)
Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert D. Nowak
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation. ICLR (2024)
Jeongyeol Kwon, Shie Mannor, Constantine Caramanis, Yonathan Efroni
RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation. CoRR (2024)
Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert D. Nowak, Yixuan Li
Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection. ICML (2023)
Jeongyeol Kwon, Dohyun Kwon, Steve Wright, Robert D. Nowak
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation. CoRR (2023)
Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert D. Nowak
A Fully First-Order Method for Stochastic Bilevel Optimization. CoRR (2023)
Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis
Prospective Side Information for Latent MDPs. CoRR (2023)
Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert D. Nowak
A Fully First-Order Method for Stochastic Bilevel Optimization. ICML (2023)
Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert D. Nowak, Yixuan Li
Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection. CoRR (2023)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Reward-Mixing MDPs with Few Latent Contexts are Learnable. ICML (2023)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Tractable Optimality in Episodic Latent MABs. CoRR (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. ICML (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. CoRR (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Tractable Optimality in Episodic Latent MABs. NeurIPS (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Reward-Mixing MDPs with a Few Latent Contexts are Learnable. CoRR (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Reinforcement Learning in Reward-Mixing MDPs. NeurIPS (2021)
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. AISTATS (2021)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
RL for Latent MDPs: Regret Guarantees and a Lower Bound. NeurIPS (2021)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Reinforcement Learning in Reward-Mixing MDPs. CoRR (2021)
Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
On the computational and statistical complexity of over-parameterized matrix sensing. CoRR (2021)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
RL for Latent MDPs: Regret Guarantees and a Lower Bound. CoRR (2021)
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. CoRR (2020)
Jeongyeol Kwon, Constantine Caramanis
EM Algorithm is Sample-Optimal for Learning Mixtures of Well-Separated Gaussians. CoRR (2020)
Jeongyeol Kwon, Constantine Caramanis
EM Converges for a Mixture of Many Linear Regressions. AISTATS (2020)
Jeongyeol Kwon, Constantine Caramanis
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians. COLT (2020)
Jeongyeol Kwon, Wei Qian, Constantine Caramanis, Yudong Chen, Damek Davis
Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression. COLT (2019)
Jeongyeol Kwon, Constantine Caramanis
EM Converges for a Mixture of Many Linear Regressions. CoRR (2019)
Jeongyeol Kwon, Constantine Caramanis
Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression. CoRR (2018)