Publications associées à Algorithme du gradient stochastique

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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

Algorithme du gradient stochastique

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On the Generalization of Stochastic Gradient Descent with Momentum

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Understanding generalization and robustness in modern deep learning

Explainable Face Verification via Feature-Guided Gradient Backpropagation

Scalable constrained optimization

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Revisiting Character-level Adversarial Attacks for Language Models

Topics in statistical physics of high-dimensional machine learning

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Robust machine learning for neuroscientific inference

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Scalable constrained optimization

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Topics in statistical physics of high-dimensional machine learning

Robust machine learning for neuroscientific inference

On the Generalization of Stochastic Gradient Descent with Momentum

Explainable Face Verification via Feature-Guided Gradient Backpropagation

Understanding generalization and robustness in modern deep learning

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Revisiting Character-level Adversarial Attacks for Language Models