Previous Conferences & Workshops

Some words in the title are between quotation marks because it is a matter of interpretation. For dynamical systems on finite dimensional spaces, one often equates observable events with positive Lebesgue measure sets, and invariant distributions...

Suppose L is a link with n components and the rank of Kh(L;Z/2) is 2^n, we show that L can be obtained by disjoint unions and connected sums of Hopf links and unknots. This result gives a positive answer to a question asked by Batson-Seed, and...

The Information Bottleneck (IB) is an information theoretic framework for optimal representation learning. It stems from the problem of finding minimal sufficient statistics in supervised learning, but has insightful implications for Deep Learning...

We prove that, unconditionally, for all constants a, NQP = NTIME[n^polylog(n)] cannot be (1/2 + 2^(-log^a n) )-approximated by 2^(log^a n)-size ACC^0 circuits. Previously, it was even open whether E^NP can be (1/2+1/sqrt(n))-approximated by AC^0[2]...

In this talk, we will introduce a new technique of isolating the cuspidal part, or more general cuspidal components, from the $L^2$ spectrum on the spectral side of the trace formula. As an application, we prove the global Gan-Gross-Prasad and...

Protein-based drugs are becoming some of the most important drugs of the XXI century. The typical mechanism of action of these drugs is a strong protein-protein interaction (PPI) between surfaces with complementary geometry and chemistry. Over the...

I will introduce a math problem from deep learning regarding the regularization effect of gradient flow dynamics for underdetermined problems.

People learn in fast and flexible ways that elude the best artificial neural networks. Once a person learns how to “dax,” they can effortlessly understand how to “dax twice” or “dax vigorously” thanks to their compositional skills. In this talk, we...

This (mostly expository) talk will be about invariant theory viewed through the lens of computational complexity. Invariant theory is the study of symmetries, captured by group actions, by polynomials that are “invariant.” Invariant theory has had a...