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2020 – today
- 2023
[i11]Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert D. Nowak:
A Fully First-Order Method for Stochastic Bilevel Optimization. CoRR abs/2301.10945 (2023)- 2022
- [c7]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. ICML 2022: 11772-11789 - [i10]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. CoRR abs/2201.12700 (2022) - [i9]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Reward-Mixing MDPs with a Few Latent Contexts are Learnable. CoRR abs/2210.02594 (2022) - [i8]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Tractable Optimality in Episodic Latent MABs. CoRR abs/2210.03528 (2022) - 2021
- [c6]Jeongyeol Kwon, Nhat Ho, Constantine Caramanis:
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. AISTATS 2021: 1405-1413 - [c5]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Reinforcement Learning in Reward-Mixing MDPs. NeurIPS 2021: 2253-2264 - [c4]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
RL for Latent MDPs: Regret Guarantees and a Lower Bound. NeurIPS 2021: 24523-24534 - [i7]Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis:
On the computational and statistical complexity of over-parameterized matrix sensing. CoRR abs/2102.02756 (2021) - [i6]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
RL for Latent MDPs: Regret Guarantees and a Lower Bound. CoRR abs/2102.04939 (2021) - [i5]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Reinforcement Learning in Reward-Mixing MDPs. CoRR abs/2110.03743 (2021) - 2020
- [c3]Jeongyeol Kwon, Constantine Caramanis:
EM Converges for a Mixture of Many Linear Regressions. AISTATS 2020: 1727-1736 - [c2]Jeongyeol Kwon, Constantine Caramanis:
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians. COLT 2020: 2425-2487 - [i4]Jeongyeol Kwon, Constantine Caramanis:
EM Algorithm is Sample-Optimal for Learning Mixtures of Well-Separated Gaussians. CoRR abs/2002.00329 (2020) - [i3]Jeongyeol Kwon, Nhat Ho, Constantine Caramanis:
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. CoRR abs/2006.02601 (2020)
2010 – 2019
- 2019
- [c1]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: 2055-2110 - [i2]Jeongyeol Kwon, Constantine Caramanis:
EM Converges for a Mixture of Many Linear Regressions. CoRR abs/1905.12106 (2019) - 2018
- [i1]Jeongyeol Kwon, Constantine Caramanis:
Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression. CoRR abs/1810.05752 (2018)
Coauthor Index
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