Dibyakanti Kumar
@dkumar9.bsky.social
PhD @ University of Manchester.
IIT Guwahati'22.
dibyakanti.github.io
IIT Guwahati'22.
dibyakanti.github.io
Reposted by Dibyakanti Kumar
Why does noisy gradient-descent train neural nets? This fundamental question in ML remains unclear.
In our hugely revised draft my student @dkumar9.bsky.social gives the full proof that a form of noisy-GD, Langevin Monte-Carlo (#LMC), can learn arbitrary depth 2 nets.
arxiv.org/abs/2503.10428
In our hugely revised draft my student @dkumar9.bsky.social gives the full proof that a form of noisy-GD, Langevin Monte-Carlo (#LMC), can learn arbitrary depth 2 nets.
arxiv.org/abs/2503.10428
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 ...
arxiv.org
August 22, 2025 at 3:59 PM
Why does noisy gradient-descent train neural nets? This fundamental question in ML remains unclear.
In our hugely revised draft my student @dkumar9.bsky.social gives the full proof that a form of noisy-GD, Langevin Monte-Carlo (#LMC), can learn arbitrary depth 2 nets.
arxiv.org/abs/2503.10428
In our hugely revised draft my student @dkumar9.bsky.social gives the full proof that a form of noisy-GD, Langevin Monte-Carlo (#LMC), can learn arbitrary depth 2 nets.
arxiv.org/abs/2503.10428
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.
In my recent work with @anirbit.bsky.social and Samyak Jha (arxiv.org/abs/2503.10428), we prove noisy gradient descent learns neural nets.
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 ...
arxiv.org
March 19, 2025 at 11:29 AM
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.
In my recent work with @anirbit.bsky.social and Samyak Jha (arxiv.org/abs/2503.10428), we prove noisy gradient descent learns neural nets.