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Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Laboratoire de traitement des signaux 4

Graph Chatbot

Chattez avec Graph Search

Topics in statistical physics of high-dimensional machine learning

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Scalable constrained optimization

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

A ride time-oriented scheduling algorithm for dial-a-ride problems

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Data-Driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

From low-rank retractions to dynamical low-rank approximation and back

A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation

Topics in statistical physics of high-dimensional machine learning

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Scalable constrained optimization

A ride time-oriented scheduling algorithm for dial-a-ride problems

From low-rank retractions to dynamical low-rank approximation and back

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

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

Data-Driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation