Dibyakanti Kumar

Langevin Monte-Carlo Provably Learns Depth Two Neural Nets at Any Size and Data In this work, we will establish that the Langevin Monte-Carlo algorithm can learn depth-2 neural nets of any size and for any data and we give non-asymptotic convergence rates for it. We achieve this ...

Noisy gradient descent has attracted a lot of attention in the last few years as a mathematically tractable model of actual deep-learning algorithms.

In my recent work with @anirbit.bsky.social and Samyak Jha (arxiv.org/abs/2503.10428), we prove noisy gradient descent learns neural nets.