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Machine à vecteurs de support

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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

Machine à vecteurs de support

Graph Chatbot

Chattez avec Graph Search

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Match Normalization: Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World

Partial discharge localization in power transformer tanks using machine learning methods

The complexity of quantum support vector machines

Topics in statistical physics of high-dimensional machine learning

Toward plasma drifts in EMC3: Implementation of gradient, divergence, and particle tracing schemes

Error scaling laws for kernel classification under source and capacity conditions

Data Downloaded via Parachute from a NASA Super-Pressure Balloon

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Match Normalization: Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World

Topics in statistical physics of high-dimensional machine learning

Error scaling laws for kernel classification under source and capacity conditions

Data Downloaded via Parachute from a NASA Super-Pressure Balloon

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Partial discharge localization in power transformer tanks using machine learning methods

The complexity of quantum support vector machines

Toward plasma drifts in EMC3: Implementation of gradient, divergence, and particle tracing schemes