144 citations · 1.1k across the 52 of their papers we have counts for
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Imitation Learning from Purified Demonstrations
Yunke Wang, Minjing Dong, Yukun Zhao +2
Imitation learning has emerged as a promising approach for addressing sequential decision-making problems, with the assumption that expert demonstrations are optimal. However, in r…
A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo +2
Deep neural networks are increasingly utilized in various machine learning tasks. However, as these models grow in complexity, they often face calibration issues, despite enhanced…
Dual Focal Loss for Calibration
Linwei Tao, Minjing Dong, Chang Xu
The use of deep neural networks in real-world applications require well-calibrated networks with confidence scores that accurately reflect the actual probability. However, it has b…
Unlabeled Imperfect Demonstrations in Adversarial Imitation Learning
Yunke Wang, Bo Du, Chang Xu
Adversarial imitation learning has become a widely used imitation learning framework. The discriminator is often trained by taking expert demonstrations and policy trajectories as…