PRiML Seminar: “Optimizing probability distributions for learning: sampling meets optimization”
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Room 401B, 3401 Walnut
3401 Walnut Street, Philadelphia, PA, United States
Optimization and sampling are both of central importance in large-scale machine learning problems, but they are typically viewed as very different problems. This talk presents recent results that exploit the interplay between them. Viewing Markov chain Monte Carlo sampling algorithms as performing an optimization over the space of probability distributions, we demonstrate analogs of Nesterov's acceleration approach in the sampling domain, […]

