Publications associées à Metrizing Fairness

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Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Patrick Thiran, Negar Kiyavash, Saber Salehkaleybar

We study the performance of Stochastic Cubic Regularized Newton (SCRN) on a class of functions satisfying gradient dominance property with

1\le\alpha\le2

which holds in a wide range of applications in machine learning and signal processing. This conditio ...

NeurIPS2022

Metrizing Fairness

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Topics in statistical physics of high-dimensional machine learning

Understanding generalization and robustness in modern deep learning

Communication-efficient distributed training of machine learning models

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

Masked Training of Neural Networks with Partial Gradients

Momentum-Based Policy Gradient with Second-Order Information

The role of convolutional neural networks in scanning probe microscopy: a review

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Topics in statistical physics of high-dimensional machine learning

Masked Training of Neural Networks with Partial Gradients

Momentum-Based Policy Gradient with Second-Order Information

The role of convolutional neural networks in scanning probe microscopy: a review

Understanding generalization and robustness in modern deep learning

Communication-efficient distributed training of machine learning models

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization