Kimin Lee

I'm a research scientist at Google Research. Previously, I was a postdoc at UC Berkeley (advised by Pieter Abbeel), and I received my PhD at Korea Advanced Institute of Science and Technology (advised by Jinwoo Shin). During PhD, I also interned and collaborated closely with Honglak Lee at University of Michigan.

  • Contact: kiminl at google dot com // pokaxpoka at gmail dot com

Publications (C: conference / J: journal / P: preprint / *: equal contribution / ^: equal advising)

2022

[C34] Reinforcement Learning with Action-Free Pre-Training from Videos [pdf][code]

[C33] SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning [pdf]

[C32] Reward Uncertainty for Exploration in Preference-based Reinforcement Learning [pdf]

[C31] Towards More Generalizable One-shot Visual Imitation Learning [pdf]

[C30] Programmatic Modeling and Generation of Real-time Strategic Soccer Environments for Reinforcement Learning [pdf]

2021

[C29] B-Pref: Benchmarking Preference-Based Reinforcement Learning [pdf][code]

[C28] URLB: Unsupervised Reinforcement Learning Benchmark [pdf][code]

[C27] Decision Transformer: Reinforcement Learning via Sequence Modeling [pdf][code]

[C26] Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings [pdf][code]

[C25] Improving Transferability of Representations via Augmentation-Aware Self-Supervision [pdf][code]

[C24] Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback [pdf][code]

[C23] Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble [pdf][code]

  • Seunghyun Lee*, Younggyo Seo*, Kimin Lee, Pieter Abbeel, Jinwoo Shin

  • Conference on Robot Learning (CoRL) 2021

  • Previous version [pdf] in NeurIPS Workshop on Offline RL 2020 as Oral presentation & NeurIPS Workshop on Deep RL 2020

[C22] PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training [pdf][code][site]

[C21] State Entropy Maximization with Random Encoders for Efficient Exploration [pdf][code][site]

[C20] SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning [pdf][code]

[C19] Decoupling Representation Learning from Reinforcement Learning [pdf][code]

[C18] Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environments [pdf][podcast]

[C17] Learning to Sample with Local and Global Contexts in Experience Replay Buffer [pdf][code]

[C16] MASKER: Masked Keyword Regularization for Reliable Text Classification [pdf][code]

2020

[C15] Reinforcement Learning with Augmented Data [pdf][code][blog] [media]

[C14] Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning [pdf][code][site]

[C13] Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning [pdf][code][site]

[C12] Regularizing Class-wise Predictions via Self-knowledge Distillation [pdf] [code]

[C11] Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning [pdf] [code]

[P3] R-LAtte: Visual Control via Deep Reinforcement Learning with Attention Network [pdf]

  • Mandi Zhao, Qiyang Li, Aravind Srinivas, Ignasi Clavera, Kimin Lee, Pieter Abbeel

  • NeurIPS Workshop on Deep RL 2020

[P2] Dynamics Generalization via Information Bottleneck in Deep Reinforcement Learning [pdf]

    • Xingyu Lu, Kimin Lee, Pieter Abbeel, Stas Tiomkin

    • Arxiv preprint 2020

2019

[C10] Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild [pdf][code]

[C9] Robust Inference via Generative Classifiers for Handling Noisy Labels [pdf][code]

[C8] Using Pre-Training Can Improve Model Robustness and Uncertainty [pdf] [code]

[J1] Dynamic Control for On-demand Interference-managed WLAN Infrastructures [pdf]

    • Seokhyun Kim, Kimin Lee, Yeonkeun Kim, Jinwoo Shin, Seungwon Shin, Song Chong

    • IEEE/ACM Transactions on Networking (TON) 2019

2018

[C7] A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks [pdf] [code]

[C6] Learning to Specialize with Knowledge Distillation for Visual Question Answering [pdf] [code]

[C5] Hierarchical Novelty Detection for Visual Object Recognition [pdf] [code]

[C4] Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples [pdf] [code]

2017

[C3] Confident Multiple Choice Learning [pdf] [code]

[P1] Simplified Stochastic Feedforward Neural Networks [pdf]

    • Kimin Lee, Jaehyung Kim, Song Chong, Jinwoo Shin

    • Arxiv preprint 2017

2016

[C2] TravelMiner: On the Benefit of Path-based Mobility Prediction

[C1] Just-in-time WLANs: On-demand Interference-managed WLAN Infrastructures [pdf] [slides]

Education

  • 2015.02-2020.02: Doctor of Philosophy (Ph.D.), School of Electrical Engineering (Machine/deep learning), KAIST (adviser: Jinwoo Shin)

  • 2013.02-2015.02: Master of Science (MS), School of Electrical Engineering (Wireless communication networks), KAIST (adviser: Song Chong and Jinwoo Shin)

  • 2009.02-2013.02: Bachelor of Engineering (BS), School of Electrical Engineering, KAIST

Academic Activities

  • Area chair

    • NeurIPS Datasets and Benchmarks

  • Conference reviewer

    • NeurIPS, ICML, ICLR, AAAI, ICRA, RSS, CoRL, UAI, IJCAI, CoLLAs, ACML

  • Journal reviewer

    • Journal of Machine Learning Research, IEEE Transactions on Pattern Analysis and Machine Intelligence, Transactions on Machine Learning Research, IEEE Robotics and Automation Letters, IEEE/ACM Transactions on Networking

  • Workshop organizer

    • Deep Reinforcement Learning Workshop, NeurIPS 2020

  • Admissions committee

    • UC Berkeley EECS, 2020

Work Experience

  • 2022.02 - current: Research scientist at Google Research

  • 2020.02 - 2022.01: Postdoctoral fellow at UC Berkeley (working with Pieter Abbeel)

  • 2019.04 - 2019.09: Visiting student at University of Michigan (working with Honglak Lee)

  • 2018.06 - 2018.10: Visiting student at UC Berkeley (working with Dawn Song and Bo Li)

Mentoring

  • Current

    • Jongjin Park (PhD student at KAIST)

    • Younggyo Seo (PhD student at KAIST / Visiting PhD student at UC Berkeley)

  • Past

    • Lili Chen (BS student at UC Berkeley --> PhD student at CMU)

    • Seunghyun Lee (MS student at KAIST --> Research scientist at Riiid)

    • Xinran Liang (BS student at UC Berkeley --> PhD student at Princeton)

    • Anika Ramachandran (BS student at UC Berkeley)

    • Katherine Shu (BS student at UC Berkeley)

Selected Honor

  • Best doctoral thesis award from KAIST EE

  • Excellent research achievement award from Samsung Advanced Institute of Technology