Statistics Seminar - Dmitriy (Tim) Kunisky

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Event Date

Location
Mathematical Sciences Building 1147

Speaker: Dmitriy (Tim) Kunisky, Post-Doctoral Associate, Yale University

Title: "The computational cost of detecting hidden structures: from random to deterministic"

Abstract: 

I will present a line of work on the computational complexity of algorithmic tasks on random inputs, including hypothesis testing, sampling, and certifying bounds on optimization problems. Surprisingly, these diverse tasks admit a unified analysis involving the same two main ingredients. The first is the study of algorithms that output low-degree polynomial functions of their inputs. Such algorithms are believed to be optimal for many statistical tasks and can be understood with the theory of orthogonal polynomials, leading to strong evidence for the difficulty of certain hypothesis testing problems. The second is a strategy of "planting" unusual structures in problem instances, which shows that algorithms for sampling and certification can be interpreted as implicitly performing hypothesis testing. I will focus on examples of hypothesis testing related to principal component analysis (PCA), and their connections with problems motivated by statistical physics: (1) sampling from Ising models, and (2) certifying bounds on random functions associated with models of spin glasses.

Next, I will describe more recent results probing the computational cost of certification not just in random settings under strong distributional assumptions, but also for more generic problem instances. As an extreme example, by considering the sum-of-squares hierarchy of semidefinite programs, I will show how some of the above ideas may be completely derandomized and applied in a deterministic setting. Using as a testbed the long-standing open problem of computing the clique number of the number-theoretic Paley graph, I will give an analysis of semidefinite programming that leads both to new approaches to this combinatorial optimization problem and to refined notions of pseudorandomness capturing deterministic versions of phenomena from random matrix theory and free probability.


Seminar Date/Time: Wednesday January 31, 2024 at 11:00am

Location: MSB 1147

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