Events Calendar

YINS Distinguished Lecturer: Vahab Mirrokni (Google)

YINS Distinguished Lecturer: Vahab Mirrokni (Google)

Event time: 
Wednesday, September 27, 2017 - 12:00pm to 1:30pm
Location: 
Yale Institute for Network Science See map
17 Hillhouse Avenue, 3rd floor
New Haven, CT 06511
Event description: 

“Distribution Optimization and Graph Mining at Scale”

Speaker: Vahab Mirrokni
Principal Scientist, heading the algorithms research groups at Google Research

Abstract: In this talk, I will present an overview of our research efforts in the context of distributed optimization and large-scale graph mining at Google New York. In one part, I will present a general technique in distributed optimization, and show how we can get distributed approximation algorithms for clustering, submodular optimization, maximum coverage, and column subset selection problems. In the other part, I will discuss our large-scale graph mining project. In particular, I will discuss combined algorithmic and distributed system challenges in developing a large-scale graph mining library for analyzing massive graphs with trillions of edges. Here, we discuss developing the most scalable balanced partitioning and connected component tools, and a new graph processing framework based on asynchronous message passing. Time-permitting, I will touch upon on related topics such as ego-net data mining, and public-private graph computation model.

Bio: Vahab Mirrokni is a principal scientist, heading the algorithms research groups at Google Research, New York. The group consist of three main sub-teams: market algorithms, large-scale graph mining, and large-scale optimization. He received his PhD from MIT in 2005 and his B.Sc. from Sharif University of Technology in 2001. He joined Google Research in 2008, after spending a couple of years at Microsoft Research, MIT and Amazon.com. He is the co-winner of paper awards at KDD’15, ACM EC’08, and SODA’05. His research areas include algorithms, distributed and stochastic optimization, and computational economics. At Google, he is mainly working on algorithmic and economic problems related to search and online advertising. Recently he is working on online ad allocation problems, distributed algorithms for large-scale graph mining, and mechanism design for advertising exchanges.

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