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Kimin Lee
Kimin Lee
KAIST
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Año
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
23342018
Decision transformer: Reinforcement learning via sequence modeling
L Chen, K Lu, A Rajeswaran, K Lee, A Grover, M Laskin, P Abbeel, ...
Advances in neural information processing systems, 2021
18152021
Training confidence-calibrated classifiers for detecting out-of-distribution samples
K Lee, H Lee, K Lee, J Shin
International Conference on Learning Representations, 2017
10842017
Using pre-training can improve model robustness and uncertainty
D Hendrycks, K Lee, M Mazeika
International conference on machine learning, 2712-2721, 2019
9012019
Reinforcement learning with augmented data
M Laskin, K Lee, A Stooke, L Pinto, P Abbeel, A Srinivas
Advances in neural information processing systems, 2020
7962020
Decoupling representation learning from reinforcement learning
A Stooke, K Lee, P Abbeel, M Laskin
International conference on machine learning, 9870-9879, 2021
3862021
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
3572020
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training
K Lee, L Smith, P Abbeel
International Conference on Machine Learning, 2021
3022021
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
2652019
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
2632021
Aligning text-to-image models using human feedback
K Lee, H Liu, M Ryu, O Watkins, Y Du, C Boutilier, P Abbeel, ...
arXiv preprint arXiv:2302.12192, 2023
2342023
Network randomization: A simple technique for generalization in deep reinforcement learning
K Lee, K Lee, J Shin, H Lee
International Conference on Learning Representations, 2019
2282019
Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble
S Lee, Y Seo, K Lee, P Abbeel, J Shin
Annual Conference on Robot Learning, 2021
2142021
Dpok: Reinforcement learning for fine-tuning text-to-image diffusion models
Y Fan, O Watkins, Y Du, H Liu, M Ryu, C Boutilier, P Abbeel, ...
Advances in Neural Information Processing Systems 36, 79858-79885, 2023
1872023
URLB: Unsupervised reinforcement learning benchmark
M Laskin, D Yarats, H Liu, K Lee, A Zhan, K Lu, C Cang, L Pinto, P Abbeel
Conference on Neural Information Processing Systems Datasets and Benchmarks …, 2021
1692021
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
1642019
State entropy maximization with random encoders for efficient exploration
Y Seo, L Chen, J Shin, H Lee, P Abbeel, K Lee
International Conference on Machine Learning, 2021
1532021
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
1492020
Masked world models for visual control
Y Seo, D Hafner, H Liu, F Liu, S James, K Lee, P Abbeel
Conference on Robot Learning, 1332-1344, 2023
1392023
B-Pref: Benchmarking Preference-Based Reinforcement Learning
K Lee, L Smith, A Dragan, P Abbeel
Conference on Neural Information Processing Systems Datasets and Benchmarks …, 2021
1312021
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