Date: 31st August 2023
Time: 04:00-05:00 pm

Venue: Physics Department conference room and https://meet.google.com/kmd-amjr-zgp

Speaker: Dr. Swapnamay Mondal, Dublin Institute for Advanced Studies, Ireland

Title: Black Holes and the loss landscape in machine learning

Abstract:

Understanding the loss landscape is an important problem in machine learning. One key feature of the loss function, common to many neural network architectures, is the presence of exponentially many low-lying local minima. Physical systems with similar energy landscapes may provide useful insights.

Black holes naturally give rise to such landscapes, owing to the existence of black hole entropy. For definiteness, we consider 1/8 BPS black holes in N = 8 string theory. These provide an infinite family of potential landscapes arising in the microscopic descriptions of corresponding black holes. The counting of minima amounts to black hole microstate counting. Moreover, the exact numbers of the minima for these landscapes are a priori known from dualities in string theory. We estimate the number of runs needed to find all the minima. Initial explorations suggest that Stochastic Gradient Descent can find a significant fraction of the minima.