Publications associées à Distributed Inference Over Networks Under Subspace Constraints

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Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Nicolas Henri Bernard Flammarion, Hristo Georgiev Papazov, Scott William Pesme

In this work, we investigate the effect of momentum on the optimisation trajectory of gradient descent. We leverage a continuous-time approach in the analysis of momentum gradient descent with step size

\gamma

and momentum parameter

\beta

that allows u ...

2024

Distributed Inference Over Networks Under Subspace Constraints

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Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

A ride time-oriented scheduling algorithm for dial-a-ride problems

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Understanding generalization and robustness in modern deep learning

Spectral Estimators for High-Dimensional Matrix Inference

Stochastic adaptive resampling for the estimation of discrete choice models

Universal and adaptive methods for robust stochastic optimization

Robust Collaborative Learning with Linear Gradient Overhead

Phenomenological theory of variational quantum ground-state preparation

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

A ride time-oriented scheduling algorithm for dial-a-ride problems

Understanding generalization and robustness in modern deep learning

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Stochastic adaptive resampling for the estimation of discrete choice models

Spectral Estimators for High-Dimensional Matrix Inference

Universal and adaptive methods for robust stochastic optimization

Robust Collaborative Learning with Linear Gradient Overhead

Phenomenological theory of variational quantum ground-state preparation