The goal of this workshop is to provide the attendees with a primer on some well-known classical families of polynomials (mostly Chebyshev, Hermite, and Laguerre), and their possible applications to various areas of Theoretical Computer Science -- in particular in learning, circuit complexity, and property testing. More specifically, the aim is to describe the main properties of each of these polynomials, and build a high-level intuition and understanding of why they can be useful, and which one to think of and use in which situation. More detailed topics would include (a) characterizations and specifics of each of the standard families of orthogonal polynomials, and (b) specific constructions and arguments relying on these polynomials in different subfields (e.g., approximation theory, distribution testing).

Schedule (Tentative)


Justin Thaler
Justin Thaler received his PhD at Harvard University under the supervision of Michael Mitzenmacher, and is currently an Assistant Professor at Georgetown University. His research focuses on algorithms for massive data sets, verifiable computation, and computational learning theory.
Paul Valiant
Paul Valiant received his PhD at MIT under the supervision of Silvio Micali, and is currently an Assistant Professor at Brown University. His research focuses on the theory behind big data, scientific computing, and evolution.
Nisheeth Vishnoi
Nisheeth Vishnoi received his PhD at Georgia Tech under the supervision of Richard Lipton, and is currently a Professor at EPFL. His research focuses on algorithms, complexity, and optimization, including on how computation can be used to gain insight into processes in nature and society.

Organizers and support

This workshop is organized by Clément Canonne and Gautam "G" Kamath, with the support of the FOCS Tutorial and Workshop chairs Alexandr Andoni and Aleksander Madry.