Kimin Lee
Kimin Lee
Postdoc, UC Berkeley
Verified email at berkeley.edu - Homepage
Title
Cited by
Cited by
Year
A simple unified framework for detecting out-of-distribution samples and adversarial attacks
K Lee, K Lee, H Lee, J Shin
Advances in neural information processing systems 31, 2018
5392018
Training confidence-calibrated classifiers for detecting out-of-distribution samples
K Lee, H Lee, K Lee, J Shin
arXiv preprint arXiv:1711.09325, 2017
4072017
Using pre-training can improve model robustness and uncertainty
D Hendrycks, K Lee, M Mazeika
International Conference on Machine Learning, 2712-2721, 2019
2472019
Reinforcement learning with augmented data
M Laskin, K Lee, A Stooke, L Pinto, P Abbeel, A Srinivas
arXiv preprint arXiv:2004.14990, 2020
1212020
Overcoming catastrophic forgetting with unlabeled data in the wild
K Lee, K Lee, J Shin, H Lee
Proceedings of the IEEE/CVF International Conference on Computer Vision, 312-321, 2019
642019
Network randomization: A simple technique for generalization in deep reinforcement learning
K Lee, K Lee, J Shin, H Lee
arXiv preprint arXiv:1910.05396, 2019
552019
Regularizing class-wise predictions via self-knowledge distillation
S Yun, J Park, K Lee, J Shin
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
542020
Decoupling representation learning from reinforcement learning
A Stooke, K Lee, P Abbeel, M Laskin
International Conference on Machine Learning, 9870-9879, 2021
442021
Robust inference via generative classifiers for handling noisy labels
K Lee, S Yun, K Lee, H Lee, B Li, J Shin
International Conference on Machine Learning, 3763-3772, 2019
42*2019
Hierarchical novelty detection for visual object recognition
K Lee, K Lee, K Min, Y Zhang, J Shin, H Lee
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
382018
Confident Multiple Choice Learning
K Lee, C Hwang, KS Park, J Shin
Proceedings of the 34th International Conference on Machine Learning, 2017
382017
Sunrise: A simple unified framework for ensemble learning in deep reinforcement learning
K Lee, M Laskin, A Srinivas, P Abbeel
International Conference on Machine Learning, 6131-6141, 2021
332021
Learning to Specialize with Knowledge Distillation for Visual Question Answering.
J Mun, K Lee, J Shin, B Han
NeurIPS, 8092-8102, 2018
222018
Decision transformer: Reinforcement learning via sequence modeling
L Chen, K Lu, A Rajeswaran, K Lee, A Grover, M Laskin, P Abbeel, ...
arXiv preprint arXiv:2106.01345, 2021
212021
Context-aware dynamics model for generalization in model-based reinforcement learning
K Lee, Y Seo, S Lee, H Lee, J Shin
International Conference on Machine Learning, 5757-5766, 2020
202020
State entropy maximization with random encoders for efficient exploration
Y Seo, L Chen, J Shin, H Lee, P Abbeel, K Lee
arXiv preprint arXiv:2102.09430, 2021
152021
TravelMiner: on the benefit of path-based mobility prediction
J Jeong, K Lee, B Abdikamalov, K Lee, S Chong
2016 13th Annual IEEE International Conference on Sensing, Communication …, 2016
82016
Just-in-time WLANs: On-demand interference-managed WLAN infrastructures
K Lee, Y Kim, S Kim, J Shin, S Shin, S Chong
IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer …, 2016
7*2016
Trajectory-wise multiple choice learning for dynamics generalization in reinforcement learning
Y Seo, K Lee, I Clavera, T Kurutach, J Shin, P Abbeel
arXiv preprint arXiv:2010.13303, 2020
52020
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings
L Chen, K Lee, A Srinivas, P Abbeel
arXiv preprint arXiv:2103.02886, 2021
42021
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Articles 1–20