Publications

Preprints

• Tractable and Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
  • Taehyun Cho, Seungyub Han, Seokhun Ju, Dohyeong Kim, Kyungjae Lee, Jungwoo Lee
  • ICLR 2025 (In Submission)
• Policy-labeled Preference Learning: Is Preference Enough for online RLHF?
  • Taehyun Cho, Seokhun Ju, Seungyub Han, Dohyeong Kim, Kyungjae Lee, Jungwoo Lee
• Distributionally Robust Regret

Conferences

• Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees
  • Dohyeong Kim, Taehyun Cho, Seungyub Han, Hojun Chung, Kyungjae Lee, Songhwai Oh
  • NeurIPS 2024
• Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion
  • Taehyun Cho, Seungyub Han, Heesoo Lee, Kyungjae Lee, Jungwoo Lee
  • NeurIPS 2023
  • [Paper] / [Arxiv]
• SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning
  • Dohyeok Lee, Seungyub Han, Taehyun Cho, Jungwoo Lee
  • NeurIPS 2023
  • [Paper] / [Arxiv]
• On the Convergence of Continual Learning with Adaptive Methods
  • Seungyub Han, Yeongmo Kim, Taehyun Cho, Jungwoo Lee
  • UAI 2023
  • [Paper]
• Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication
  • Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Taehyun Cho, Jungwoo Lee
  • ICML 2021
  • [Paper]

Journals

• Optimized Shallow Neural Networks for Sum-rate Maximization in Energy Harvesting Downlink Multiuser NOMA Systems
  • Heasung Kim, Taehyun Cho, Jungwoo Lee, Wonjae Shin, H Vincent Poor
  • IEEE Journal on Selected Areas in Communications
  • [Paper]
• An Efficient Neural Network Architecture for Rate Maximization in Energy Harvesting Downlink Channels
  • Heasung Kim, Taehyun Cho, Jungwoo Lee, Wonjae Shin, H Vincent Poor
  • 2020 IEEE International Symposium on Information Theory (ISIT)
  • [Paper]