2015 - 2016

2015 Dec 02

CMSA Talk: Eero Saksman

2:00pm to 3:30pm

Location: 

Science Center 232
The uniqueness of Gaussian multiplicative chaos revisited
2016 Apr 26

STAT303Lect: Roger B. Porter

10:15am to 11:30am

Location: 

Science Center Rm. 705

Presidential Decision Making: How Decisions Are Made in the White House

Roger B. Porter, IBM Professor of Business and Government

"U.S. presidents must constantly make decisions on issues about which they are not expert.  Accordingly, they must rely on others for information, analysis, options, assessments, and recommendations.  How presidents approach this challenge has varied...

Read more about STAT303Lect: Roger B. Porter
2015 Sep 25

StochStatMIT: Edo Airoldi

11:00am to 12:00pm

Location: 

32-141
Title: Some Fundamental Ideas for Causal Inference on Large Networks Abstract: Classical approaches to causal inference largely rely on the assumption of "lack of interference", according to which the outcome of each individual does not depend on the treatment assigned to others. In many applications, however, including healthcare interventions in schools, online education, and design of online auctions and political campaigns on social media, assuming lack of interference is untenable. In this talk, Prof. Airoldi will introduce some fundamental ideas to deal with interference in causal... Read more about StochStatMIT: Edo Airoldi
2015 Sep 29

ResearchStats: Evan Greif & Viktoriya Krakovna

12:00pm to 1:00pm

Location: 

Science Center Rm. 705

Causal Inference in the Twilight Zone: Estimating the Mean Separation of a Normal Mixture

Sum-Product Networks for Unsupervised Learning in the Google Knowledge Graph

2016 Feb 16

ResearchStats: Hyungsuk Tak

12:00pm to 1:00pm

Location: 

Science Center Rm. 705
I have a dream that one day people will explore multi-modal distributions without tuning temperature: A repulsive-attractive Metropolis algorithm
2015 Oct 05

BrownCSSem: Forrest Crawford

3:30pm to 5:00pm

Location: 

Room 245, 121 South Main Street, Providence
Learning about hidden networks by tracing links: statistical approaches for network-based social epidemiology and public health Learning about hidden networks by tracing links: statistical approaches for network-based social epidemiology and public health

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