Hong Jun Jeon

22 papers A* 3A 1Journal 17Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Continual Learning as Computationally Constrained Reinforcement Learning.
Found. Trends Mach. Learn.
Saurabh Kumar, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon, Yueyang Liu, Benjamin Van Roy
2024 J jnl
Adaptive Crowdsourcing Via Self-Supervised Learning.
CoRR
Anmol Kagrecha, Henrik Marklund, Benjamin Van Roy, Hong Jun Jeon, Richard Zeckhauser
2024 J jnl
Aligning AI Agents via Information-Directed Sampling.
CoRR
Hong Jun Jeon, Benjamin Van Roy
2024 A* conf
An Information-Theoretic Analysis of In-Context Learning.
ICML
Hong Jun Jeon, Jason D. Lee, Qi Lei, Benjamin Van Roy
2024 J jnl
An Information-Theoretic Analysis of In-Context Learning.
CoRR
Hong Jun Jeon, Jason D. Lee, Qi Lei, Benjamin Van Roy
2024 J jnl
Epinet for Content Cold Start.
CoRR
Hong Jun Jeon, Songbin Liu, Yuantong Li, Jie Lyu, Hunter Song, Ji Liu, Peng Wu, Zheqing Zhu
2024 J jnl
Information-Theoretic Foundations for Machine Learning.
CoRR
Hong Jun Jeon, Benjamin Van Roy
2024 J jnl
Information-Theoretic Foundations for Neural Scaling Laws.
CoRR
Hong Jun Jeon, Benjamin Van Roy
2024 J jnl
The Need for a Big World Simulator: A Scientific Challenge for Continual Learning.
CoRR
Saurabh Kumar, Hong Jun Jeon, Alex Lewandowski, Benjamin Van Roy
2023 J jnl
Continual Learning as Computationally Constrained Reinforcement Learning.
CoRR
Saurabh Kumar, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon, Yueyang Liu, Benjamin Van Roy
2022 J jnl
An Information-Theoretic Analysis of Compute-Optimal Neural Scaling Laws.
CoRR
Hong Jun Jeon, Benjamin Van Roy
2022 A* conf
An Information-Theoretic Framework for Deep Learning.
NeurIPS
Hong Jun Jeon, Benjamin Van Roy
2022 J jnl
Is Stochastic Gradient Descent Near Optimal?
CoRR
Yifan Zhu, Hong Jun Jeon, Benjamin Van Roy
2022 J jnl
Learning latent actions to control assistive robots.
Auton. Robots
Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh
2022 J jnl
Sample Complexity versus Depth: An Information Theoretic Analysis.
CoRR
Hong Jun Jeon, Benjamin Van Roy
2021 J jnl
Learning Latent Actions to Control Assistive Robots.
CoRR
Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh
2020 A* conf
Reward-rational (implicit) choice: A unifying formalism for reward learning.
NeurIPS
Hong Jun Jeon, Smitha Milli, Anca D. Dragan
2020 J jnl
Reward-rational (implicit) choice: A unifying formalism for reward learning.
CoRR
Hong Jun Jeon, Smitha Milli, Anca D. Dragan
2020 — conf
Shared Autonomy with Learned Latent Actions.
Robotics: Science and Systems
Hong Jun Jeon, Dylan P. Losey, Dorsa Sadigh
2020 J jnl
Shared Autonomy with Learned Latent Actions.
CoRR
Hong Jun Jeon, Dylan P. Losey, Dorsa Sadigh
2018 A conf
Configuration Space Metrics.
IROS
Hong Jun Jeon, Anca D. Dragan
2018 J jnl
Configuration Space Metrics.
CoRR
Hong Jun Jeon, Anca D. Dragan