CSE Colloquium – Algorithmic Problems in Discrete Choice by Ravi Kumar

Abstract:
In discrete choice, a user selects one option from a finite set of available alternatives, a process that is crucial for recommendation systems applications in e-commerce, social media, search engines, etc.  A popular way to model discrete choice is through Random Utility Models (RUMs).  RUMs assume that users assign values to options and choose the one with the highest value from among the available alternatives.  RUMs have become increasingly important in the Web era; they offer an elegant mathematical framework for researchers to model user choices and predict user behavior based on (possibly limited)  observations.   While RUMs have been extensively studied in behavioral economics and social sciences, many basic algorithmic tasks remain poorly understood.  In this talk, we will discuss various algorithmic and learning questions concerning RUMs.

Bio: 
Ravi Kumar has been a research scientist at Google since 2012. Prior to this, he was at the IBM Almaden Research Center and at Yahoo! Research. His interests include algorithms for massive data, ML/privacy, and the theory of computation. He maintains an extensive publication record that includes Test-of-Time Awards from STOC and WWW, as well as Best Paper Awards from KDD and WWW, to mention a few. He is an ACM fellow.

Hosted by: Professor Sungjin Im

Zoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3