BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//MIT Center for Statistics - ECPv4.5.9//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:MIT Center for Statistics
X-ORIGINAL-URL:https://stat.mit.edu
X-WR-CALDESC:Events for MIT Center for Statistics
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170908T110000
DTEND;TZID=America/New_York:20170908T110000
DTSTAMP:20170824T103114
CREATED:20170801T015203Z
LAST-MODIFIED:20170809T154616Z
UID:1676-1504868400-1504868400@stat.mit.edu
SUMMARY:New provable techniques for learning and inference in probabilistic graphical models Andrej Risteski (MIT)
DESCRIPTION:A common theme in machine learning is succinct modeling of distributions over large domains. Probabilistic graphical models are one of the most expressive frameworks for doing this. The two major tasks involving graphical models are learning and inference. Learning is the task of calculating the “best fit” model parameters from raw data\, while inference is the task of answering probabilistic queries for a model with known parameters (e.g. what is the marginal distribution of a subset of variables\, after conditioning on the values of some other variables). Learning can be thought of as finding a graphical model that “explains” the raw data\, while the inference queries extract the “knowledge” the graphical model contains. \nI will focus on a few vignettes from my research which give new provable techniques for these tasks:\n– In the context of learning\, I will talk about method-of-moments techniques for learning noisy-or Bayesian networks\, which are used for modeling the causal structure of diseases and symptoms.\n– In the context of inference\, I will talk about a new understanding of a class of algorithms for calculating partition functions\, called variational methods\, through the\nlens of convex programming hierarchies. Time permitting\, I will also speak about MCMC methods for sampling from highly multimodal distributions using simulated tempering. \nThe talk will assume no background\, and is meant as a “meet and greet” talk surveying various questions I’ve worked on and am interested in. \n
URL:https://stat.mit.edu/calendar/stochastics-and-statistics-seminar-andrej-risteski/
CATEGORIES:Stochastics and Statistics Seminar
END:VEVENT
END:VCALENDAR