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04/19/2023
Leveraging the two timescale regime to demonstrate convergence of neural networks
We study the training dynamics of shallow neural networks, in a two-time...
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02/28/2023
Learning time-scales in two-layers neural networks
Gradient-based learning in multi-layer neural networks displays a number...
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08/31/2022
Incremental Learning in Diagonal Linear Networks
Diagonal linear networks (DLNs) are a toy simplification of artificial n...
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02/22/2022
Acceleration of Gossip Algorithms through the Euler-Poisson-Darboux Equation
Gossip algorithms and their accelerated versions have been studied exclu...
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09/24/2021
Graph-based Approximate Message Passing Iterations
Approximate-message passing (AMP) algorithms have become an important el...
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06/10/2021
A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip
We introduce the continuized Nesterov acceleration, a close variant of N...
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02/11/2021
A Continuized View on Nesterov Acceleration
We introduce the "continuized" Nesterov acceleration, a close variant of...
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06/15/2020
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model
In the context of statistical supervised learning, the noiseless linear ...
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05/22/2018
