Jul 17, 2020
This talk is about a new learned dynamic memory controller for organizing prior experiences in a way that is empirically useful for a number of downstream tasks. The controller supports logarithmic time operations and can thus be integrated into existing statistical learning algorithms as an augmented memory unit without substantially increasing training and inference computation. It also supports optional reward reinforcement, which brings a steady improvement empirically. The controller operates as a reduction to online classification, allowing it to benefit from advances in representation or architecture. This is joint work with Wen Sun, Hal Daume, John Langford, and Paul Mineiro (published at ICML-2019).
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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