Minchan Jeong

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 16

Top Topics

Global Knowledge

Rank Minimization

Sparse Approximation

Top Venues

Publications

Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. CoRR (2024)
Seongyoon Kim, Minchan Jeong, Sungnyun Kim, Sungwoo Cho, Sumyeong Ahn, Se-Young Yun
FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning. CoRR (2024)
Yoonji Kim, Insu Oh, Jiung Hwang, Minchan Jeong, Kangbin Yim
Effect of DoS Attack into LiDAR Ethernet. IMIS (2024)
Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. ACL (1) (2024)
Gihun Lee, Minchan Jeong, Yujin Kim, Hojung Jung, Jaehoon Oh, Sangmook Kim, Se-Young Yun
BAPO: Base-Anchored Preference Optimization for Personalized Alignment in Large Language Models. CoRR (2024)
Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. CoRR (2024)
Jongwoo Ko, Seungjoon Park, Minchan Jeong, Sukjin Hong, Euijai Ahn, Du-Seong Chang, Se-Young Yun
Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective. CoRR (2023)
Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. EMNLP (Findings) (2023)
Jihwan Oh, Joonkee Kim, Minchan Jeong, Se-Young Yun
Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning. AAMAS (2023)
Jihwan Oh, Joonkee Kim, Minchan Jeong, Se-Young Yun
Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning. CoRR (2023)
Jung-Hun Kim, Se-Young Yun, Minchan Jeong, Junhyun Nam, Jinwoo Shin, Richard Combes
Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles. AISTATS (2023)
Gihun Lee, Minchan Jeong, Sangmook Kim, Jaehoon Oh, Se-Young Yun
FedSoL: Bridging Global Alignment and Local Generality in Federated Learning. CoRR (2023)
Jongwoo Ko, Seungjoon Park, Minchan Jeong, Sukjin Hong, Euijai Ahn, Du-Seong Chang, Se-Young Yun
Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective. EACL (Findings) (2023)
Daniel Bienstock, Minchan Jeong, Apurv Shukla, Se-Young Yun
Robust Streaming PCA. NeurIPS (2022)
Gihun Lee, Minchan Jeong, Yongjin Shin, Sangmin Bae, Se-Young Yun
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning. NeurIPS (2022)
Gihun Lee, Yongjin Shin, Minchan Jeong, Se-Young Yun
Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning. CoRR (2021)