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publications
Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression
J. Kwon, W. Qian, C. Caramanis, Y. Chen, and D. DamekProceedings of the 32nd Annual Conference on Learning Theory (COLT) 2019
[Arxiv] [Conference] [Video]
EM Converges for a Mixture of Many Linear Regressions
J. Kwon and C. CaramanisProceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS) 2020
[Arxiv] [Conference]
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians
J. Kwon and C. CaramanisProceedings of the 33rd Annual Conference on Learning Theory (COLT) 2020
[Arxiv] [Conference] [Video]
On the Minimax Optimality of the EM Algorithm for Two-Component Mixed Linear Regression
J. Kwon, N. Ho and C. CaramanisProceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021
[Arxiv] [Conference]
On the Computational and Statistical Complexity of Over-Parameterized Matrix Sensing
J. Zhuo, J. Kwon, N. Ho and C. CaramanisPreprint, 2021
[Arxiv]
RL for Latent MDPs: Regret Guarantees and a Lower Bound
J. Kwon, Y. Efroni, C. Caramanis and S. MannorProceedings of the 35th Neural Information Processing Systems (NeurIPS) 2021 (Spotlight)
[Arxiv] [Conference] [RL Theory Seminar]
MLE and EM for Well-Separated Mixtures: Minimax Rates
J. Kwon and C. CaramanisWork in Progress
[Arxiv]
Reinforcement Learning in Reward-Mixing MDPs
J. Kwon, Y. Efroni, C. Caramanis and S. MannorProceedings of the 35th Neural Information Processing Systems (NeurIPS) 2021
[Arxiv] [Conference]
Coordinate Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
J. Kwon, Y. Efroni, C. Caramanis and S. MannorProceedings of the 39th International Conference on Machine Learning (ICML) 2022
[Arxiv] [Conference]
Tractable Optimality in Episodic Latent MABs
J. Kwon, Y. Efroni, C. Caramanis and S. MannorProceedings of the 36th Neural Information Processing Systems (NeurIPS) 2022
[Arxiv] [Conference]
Reward-Mixing MDPs with Few Latent Contexts are Learnable
J. Kwon, Y. Efroni, C. Caramanis and S. MannorProceedings of the 40th International Conference on Machine Learning (ICML) 2023
[Arxiv] [Conference]
Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
H. Bai, G. Canal, X. Du, J. Kwon, R. D Nowak, Y. LiProceedings of the 40th International Conference on Machine Learning (ICML) 2023
[Arxiv] [Conference]
A Fully First-Order Method for Stochastic Bilevel Optimization
J. Kwon, D. Kwon, S. Wright and R. NowakProceedings of the 40th International Conference on Machine Learning (ICML) 2023 (Oral Presentation)
[Arxiv] [Conference]
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
J. Kwon, D. Kwon, S. Wright and R. NowakarXiv Preprint
[Arxiv]
Prospective Side Information for Latent MDPs
J. Kwon, Y. Efroni, C. Caramanis and S. MannorarXiv Preprint
[Arxiv]
talks
Talk 1 on Relevant Topic in Your Field
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Talk 2 on Relevant Topic in Your Field
Conference Proceeding talk 3 on Relevant Topic in Your Field
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
Teaching experience 2
Workshop, University 1, Department, 2015