Publications associées à Efficient second-order methods for model compression

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Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection

Volkan Cevher, Anastasios Kyrillidis

The convex

\ell_1

-regularized

\log\det

divergence criterion has been shown to produce theoretically consistent graph learning. However, this objective function is challenging since the

\ell_1

-regularization is nonsmooth, the

\log\det

objective is n ...

2013

Efficient second-order methods for model compression

Graph Chatbot

Chattez avec Graph Search

Adaptive data augmentation for image classification

Sensitive and Accurate Dispersion Map Extraction of HNLFs by Frequency Tuning of a Degenerate FWM

Preconditioned Spectral Descent for Deep Learning

Multiscale Centerline Detection by Learning a Scale-Space Distance Transform

Fast Proximal Algorithms For Self-Concordant Function Minimization With Application To Sparse Graph Selection

Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection

An adaptive algorithm for the Crank-Nicolson scheme applied to a time-dependent convection-diffusion problem

Reducing computational cost and allowing automatic remeshing in FEM models of metal forming coupled with polycrystal plasticity

Une modélisation géométrique itérative basée sur les automates

Adaptive data augmentation for image classification

Reducing computational cost and allowing automatic remeshing in FEM models of metal forming coupled with polycrystal plasticity

Preconditioned Spectral Descent for Deep Learning

An adaptive algorithm for the Crank-Nicolson scheme applied to a time-dependent convection-diffusion problem

Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection

Sensitive and Accurate Dispersion Map Extraction of HNLFs by Frequency Tuning of a Degenerate FWM

Fast Proximal Algorithms For Self-Concordant Function Minimization With Application To Sparse Graph Selection

Multiscale Centerline Detection by Learning a Scale-Space Distance Transform

Une modélisation géométrique itérative basée sur les automates