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  • title: Variational Imitation Learning with Diverse-quality Demonstrations
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            Variational Imitation Learning with Diverse-quality Demonstrations
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            Variational Imitation Learning with Diverse-quality Demonstrations

            Jul 12, 2020

            Speakers

            VT

            Voot Tangkaratt

            Speaker · 0 followers

            BH

            Bo Han

            Speaker · 0 followers

            MS

            Masashi Sugiyama

            Speaker · 2 followers

            About

            Learning from demonstrations can be challenging when the quality of demonstrations is diverse, and even more so when the quality is unknown and there is no additional information to estimate the quality. We propose a new method for imitation learning in such scenarios. We show that simple quality-estimation approaches might fail due to compounding error, and fix this issue by jointly estimating both the quality and reward using a variational approach. Our method is easy to implement within reinf…

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            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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