Events Calendar

CS Colloquium: Ilias Diakonikolas (University of Edinburgh) - Algorithmic Approaches in Unsupervised Learning

Speaker: Ilias Diakonikolas, University of Edinburgh

Talk Title: Algorithmic Approaches in Unsupervised Learning

Series: CS Colloquium

Abstract: The growing scale of modern data sets and our increasingly ambitious inferential goals have highlighted new algorithmic challenges. In this talk, I will discuss recent progress in this vein that lies at the interface of computer science and statistics. I will highlight how the algorithmic perspective brings novel insights and leads to computationally efficient methods for classical statistical problems.

In this talk, I will focus on a core problem in unsupervised learning: how to infer information about a distribution based on random samples. An important goal in this context is understanding the structure in the data without making strong assumptions on its form. I will describe a unified algorithmic framework that yields new, provably efficient estimators for several natural and well-studied statistical models, including mixtures of structured distribution families (e.g., gaussian, log-concave, etc.). This framework provides a fairly complete picture of the sample and computational complexities for fundamental inference tasks, including density estimation and hypothesis testing.

I will also briefly describe some of my other work on learning, including supervised learning with missing and noisy data, as well as connections between these questions and seemingly unrelated problems in game theory and complexity theory.

The event will be available to stream HERE

Biography: Ilias Diakonikolas is an Assistant Professor in the School of Informatics at the University of Edinburgh. He holds a diploma in electrical and computer engineering from the National Technical University of Athens, and a Ph.D. in computer science from Columbia University (2010) where he was advised by Mihalis Yannakakis. He received a best thesis award for his doctoral dissertation and an honorable mention in the 2009 George Nicholson competition from the INFORMS society. Before moving to Edinburgh he spent two years (2010-2012) as the Simons postdoctoral fellow in theoretical computer science at the University of California, Berkeley. Ilias has worked in several areas of algorithms, including optimization, computational learning, and computational economics. His research focus is on the algorithmic foundations of massive data sets, in particular on designing efficient algorithms for statistics and machine learning.

Host: Computer Science Department

Location: Olin Hall of Engineering (OHE) - 132

Audiences: Everyone Is Invited

Contact: Assistant to CS chair