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Research & Seminars

Krenicki Center for Business Analytics & Machine Learning

Quantitative Methods Research Seminars:

Date Speaker Institution Topic
TBA Prof. Gabor Lugosi Department of Economics, Pompeau Fabra University TBA
September 20, 2021 Prof. Po-Ling Loh Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge TBA
August 24th, 2021 Prof. Stanislav Minsker Dep. of Mathematics, University of Southern California TBA
November 30, 2018 Prof. Simge Küçükyavuz Department of Industrial Engineering and Management Sciences, Northwestern University Risk-Averse Set Covering Problems
November 16, 2018 Prof. Emerson Melo Department of Economics, Indiana University Bloomington A Variational Approach to Network Games
October 19, 2018 Prof. Siddhartha Banerjee School of Operations Research and Information Engineering, Cornell University Online Decision-Making Using Prediction Oracles
March 23, 2018 Prof. Santanu Dey School of Industrial and Systems Engineering, Georgia Institute of Technology
Theoretical Analysis of the Role of Sparsity in Cutting-Plane Selection
March 2, 2018 Prof. Ariel Procaccia Department of Computer Science, Carnegie Mellon University Extreme Democracy
September 15, 2017 Prof. Yihong Wu Department of Statistics and Data Science, Yale University Polynomial Approximation, Moment Matching and Optimal Estimation of the Unseen
September 1, 2017 Prof. Jyrki Wallenius Aalto University School of Business Accounting for Political Opinions, Power, and Influence: A Voting Advice Application
April 28, 2017 Prof. Adam Wierman Department of Computing and Mathematical Sciences, California Institute of Technology Platforms & Networked Markets: Transparency & Market Power
November 4, 2016 Prof. Venkatesan Guruswami Department of Computer Science, Carnegie Mellon University (2+eps)-SAT is NP-Hard, and Further Results on Promise Constraint Satisfaction
September 30, 2016 Prof. Regina Liu Department of Statistics and Biostatistics, Rutgers University Fusion Learning: Fusing Inferences from Multiple Sources for More Powerful Findings

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