Publications associées à Robust Adaptive Decision Making: Bayesian Optimization and Beyond

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

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

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

Graph Chatbot

Chattez avec Graph Search

Phenomenological theory of variational quantum ground-state preparation

Stochastic adaptive resampling for the estimation of discrete choice models

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Impact of Redundancy on Resilience in Distributed Optimization and Learning

On the Privacy-Robustness-Utility Trilemma in Distributed Learning

Alternation makes the adversary weaker in two-player games

Predicting in Uncertain Environments: Methods for Robust Machine Learning

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

Approximate CVPp in time 2(0.802n)

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Phenomenological theory of variational quantum ground-state preparation

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Alternation makes the adversary weaker in two-player games

Approximate CVPp in time 2(0.802n)

Stochastic adaptive resampling for the estimation of discrete choice models

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Impact of Redundancy on Resilience in Distributed Optimization and Learning

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

On the Privacy-Robustness-Utility Trilemma in Distributed Learning

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