Adam Klivans

I am a Professor in the Computer Science Department and director of the new NSF AI Institute for Foundations of Machine Learning (IFML).

I also lead the UT-Austin Machine Learning Lab (MLL).

PUBLICATIONS

Current Students: Surbhi Goel, Sushrut Karmalkar, Aravind Gollakota.

Former Students: Pravesh Kothari , Alexander Sherstov.

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

BONUS TALK:

Moment-Matching Polynomials

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

Teaching Fall 2019: CS311 Mathematics For Computer Science

Teaching Spring 2019: CS378H Honors Data Mining

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.

Program Committees: COLT 2009 (Chair), COLT 2019, FOCS 2019.

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.

Support

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