Next Generation Variational Methods: Averaging, Tempering and Stochastic Approximations Stephan Mandt from models meaning science Watch Video
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⏲ Duration: 24 min 57 sec ✓ Published: 08-Jan-2016
Description: Bayesian modeling has become a popular approach to solving unsupervised learning problems. Mandt's team first posits a model that includes hidden patterns and then use a Bayesian inference algorithm to discover those patterns from data. There are many applications of this paradigm, including topic modeling, recommender systems, image clustering, and statistical genetics. In this talk, Mandt will first review variational inference - a fast modern algorithm that maps Bayesian inference to an optim
Play Video: (Note: The default playback of the video is HD VERSION. If your browser is buffering the video slowly, please play the REGULAR MP4 VERSION or Open The Video below for better experience. Thank you!)