Tim Roughgarden: How Computer Science Informs Modern Auction Design Tuesday, November 29, 2016  4:00pm to 5:00pm Abstract : Economists have studied the theory and practice of auctions for decades. How can computer science contribute? Using the ongoing U.S. 

Yuval Ishai: Succinct Secure Computation from DDH Tuesday, November 8, 2016  4:00pm to 5:00pm Abstract:


Ronitt Rubinfeld: Local Computation Algorithms Tuesday, November 1, 2016  4:00pm to 5:00pm Abstract: 

Muthuramakrishnana Venkitasubramaniam: Composable Adaptive Secure Protocols without Setup Under Polytime Assumptions Friday, October 28, 2016  10:30am to 12:00pm Abstract: All previous constructions of general multiparty computation protocols that are secure against adaptive corruptions in the concurrent setting either require some form of setup or nonstandard assumptions. 

Jonathan Ullman: Algorithmic Stability for Adaptive Data Analysis Tuesday, October 18, 2016  4:00pm to 5:00pm Abstract: 

Alexandr Andoni: Optimal Hashing for HighDimensional Spaces Monday, October 3, 2016  4:00pm to 5:00pm Abstract:
We survey recent advances in the approximate nearest neighbor search
problem in highdimensional Euclidean/Hamming spaces, which go beyond
the classic Locality Sensitive Hashing technique for the problem. The 

Mohsen Ghaffari: Improved Local Distributed Graph Algorithms Tuesday, September 27, 2016  4:00pm to 5:00pm Abstract: How can the computers in a network interact and communicate to solve the network's graph problems efficiently? 

Alina Ene: From Minimum Cut to Submodular Minimization: Leveraging the Decomposable Structure Monday, September 19, 2016  4:00pm to 5:00pm 

Boaz Barak: Computational Bayesianism, Sums of Squares, and Unicorns Tuesday, September 13, 2016  4:00pm to 5:00pm ABSTRACT: Can we make sense of quantities such as "the probability that 2^81712357  1 is prime" or "the probability that statement X is a logical contradiction"? 

Sebastien Bubeck: New Results at the Crossroads of Convexity, Learning and Information Theory Tuesday, October 25, 2016  3:45pm to 5:15pm Abstract: I will present three new results (no background in optimization will be assumed, all concepts will be defined and motivated): (i) the Cramer transform of the uniform measure on a convex body is a universal selfconcordant barrier; (ii) projected gradient descent with Gaussian 