Lee, Hojoon

9 publications

ICML 2025 Hyperspherical Normalization for Scalable Deep Reinforcement Learning Hojoon Lee, Youngdo Lee, Takuma Seno, Donghu Kim, Peter Stone, Jaegul Choo

ICLR 2025 SimBa: Simplicity Bias for Scaling up Parameters in Deep Reinforcement Learning Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno

ICML 2024 Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control Dongyoon Hwang, Byungkun Lee, Hojoon Lee, Hyunseung Kim, Jaegul Choo

NeurIPS 2024 Do's and Don'ts: Learning Desirable Skills with Instruction Videos Hyunseung Kim, Byungkun Lee, Hojoon Lee, Dongyoon Hwang, Donghu Kim, Jaegul Choo

ICML 2024 Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning Donghu Kim, Hojoon Lee, Kyungmin Lee, Dongyoon Hwang, Jaegul Choo

ICML 2024 Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks Hojoon Lee, Hyeonseo Cho, Hyunseung Kim, Donghu Kim, Dugki Min, Jaegul Choo, Clare Lyle

NeurIPS 2023 Learning to Discover Skills Through Guidance Hyunseung Kim, Byung Kun Lee, Hojoon Lee, Dongyoon Hwang, Sejik Park, Kyushik Min, Jaegul Choo

ICML 2023 On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning Hojoon Lee, Koanho Lee, Dongyoon Hwang, Hyunho Lee, Byungkun Lee, Jaegul Choo

NeurIPS 2023 PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning Hojoon Lee, Hanseul Cho, Hyunseung Kim, Daehoon Gwak, Joonkee Kim, Jaegul Choo, Se-Young Yun, Chulhee Yun