Adam Klivans

I am an Associate Professor in the Computer Science Department of the University of Texas at Austin.


Lectures I gave for the Real Analysis Boot Camp at the Simons Institute in September, 2013:

Analytic Methods for Supervised Learning I

Analytic Methods for Supervised Learning II

Analytic Methods for Supervised Learning III

Analytic Methods for Supervised Learning IV


Moment-Matching Polynomials

in which we suggest a notion of noise-stability for non-product distributions.

Teaching Fall 2017: CS311 Mathematics For Computer Science

Google Calendar for CS311

Teaching Spring 2016: CS363 Data Mining

NEW (FLIPPED) COURSE FOR 2013: CS313k Mathematical Tools for Computer Science, Spring 2013.

Research Professor, MSRI Workshop on Quantitative Geometry, Berkeley 2011.

PC Co-Chair: COLT 2009, in Montreal.

Editorial Board: Theory of Computing and Machine Learning Journal.

Recent Program Committees: FOCS 2007, RANDOM 2008, SODA 2009, COLT 2009 (Chair), COLT 2011, ITCS 2012, FOCS 2012, COLT 2013, FOCS 2013.

Graduate Seminar: The Computational Complexity of Machine Learning.

Current Student: Pravesh Kothari.

(Former) Student: Alexander Sherstov, Assistant Professor, UCLA.

(Former) Postdocs: Parikshit Gopalan Researcher, MSR-SVC;

Homin Lee, Senior Data Scientist, Bundle.

Research Interests:

Learning Theory, Computational Complexity, Pseudorandomness, Limit Theorems, and Gaussian Space.


Research supported by an NSF CAREER Award (The Computational Complexity of Halfspace-Based Learning), NSF Grant CCF-0728536 (The Computational Intractability of Machine Learning Tasks), and a Texas Advanced Research Program Award.

How to reach me:

E-mail: klivans@cs *dot* utexas *dot* edu

The University of Texas at Austin
Department of Computer Science
Taylor Hall 2.124
1 University Station, C0500
Austin, TX 78712-1188