Publications associées à Byzantine machine learning

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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

Byzantine machine learning

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On the Generalization of Stochastic Gradient Descent with Momentum

Universal and adaptive methods for robust stochastic optimization

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

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

Distributed Learning in Non-Convex Environments-Part I: Agreement at a Linear Rate

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms

Multi-armed Bandits in Action

Byzantine tolerant gradient descent for distributed machine learning with adversaries

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

On the Generalization of Stochastic Gradient Descent with Momentum

Byzantine tolerant gradient descent for distributed machine learning with adversaries

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

Universal and adaptive methods for robust stochastic optimization

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

Distributed Learning in Non-Convex Environments-Part I: Agreement at a Linear Rate

Multi-armed Bandits in Action