Publications associées à Graph Signal Processing for Machine Learning: A Review and New Perspectives

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

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Graph Chatbot

Chattez avec Graph Search

Robust machine learning for neuroscientific inference

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

From Nano to Macro An overview of the IEEE Bio Image and Signal Processing Technical Committee

Model agnostic methods meta-learn despite misspecifications

A Framework for Autonomic Computing for In Situ Imageomics

SKA Science Data Challenge 2: analysis and results

Algorithms push forward the application of MALDI-TOF mass fingerprinting in rapid precise diagnosis

Quantization for Distributed Processing and Learning of Structured Data

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

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

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

From Nano to Macro An overview of the IEEE Bio Image and Signal Processing Technical Committee

Robust machine learning for neuroscientific inference

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

SKA Science Data Challenge 2: analysis and results

Algorithms push forward the application of MALDI-TOF mass fingerprinting in rapid precise diagnosis

Quantization for Distributed Processing and Learning of Structured Data

A Framework for Autonomic Computing for In Situ Imageomics

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

Model agnostic methods meta-learn despite misspecifications