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SDSCon 2019 – Statistics and Data Science Conference
SDSCon 2019 is the third annual celebration of the statistics and data science community at MIT and beyond, organized by MIT’s Statistics and Data Science Center (SDSC).
Find out more »Exponential line-crossing inequalities
Aaditya Ramdas (Carnegie Mellon University)
Abstract: This talk will present a class of exponential bounds for the probability that a martingale sequence crosses a time-dependent linear threshold. Our key insight is that it is both natural and fruitful to formulate exponential concentration inequalities in this way. We will illustrate this point by presenting a single assumption and a single theorem that together strengthen many tail bounds for martingales, including classical inequalities (1960-80) by Bernstein, Bennett, Hoeffding, and Freedman; contemporary inequalities (1980-2000) by Shorack and Wellner,…
Find out more »Stochastics and Statistics Seminar
Aaron Roth (University of Pennsylvania)
MIT Statistics and Data Science Center host guest lecturers from around the world in this weekly seminar.
Find out more »Stochastics and Statistics Seminar Series
Chao Gao (University of Chicago)
MIT Statistics and Data Science Center host guest lecturers from around the world in this weekly seminar.
Find out more »Stochastics and Statistics Seminar
Tracy Ke (Harvard University)
MIT Statistics and Data Science Center host guest lecturers from around the world in this weekly seminar.
Find out more »Counting and sampling at low temperatures
Will Perkins (University of Illinois at Chicago)
Abstract: We consider the problem of efficient sampling from the hard-core and Potts models from statistical physics. On certain families of graphs, phase transitions in the underlying physics model are linked to changes in the performance of some sampling algorithms, including Markov chains. We develop new sampling and counting algorithms that exploit the phase transition phenomenon and work efficiently on lattices (and bipartite expander graphs) at sufficiently low temperatures in the phase coexistence regime. Our algorithms are based on Pirogov-Sinai…
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