Introduction to MVA approach

Balázs Kégl

Conference papers

Introduction to MVA approach

Balázs Kégl ^{1, 2}

1 TAO - Machine Learning and Optimisation

CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique

2 Appstat

LAL - Laboratoire de l'Accélérateur Linéaire, LRI - Laboratoire de Recherche en Informatique

Document type :

Conference papers

Domain :

Computer Science [cs] / Distributed, Parallel, and Cluster Computing [cs.DC]

Computer Science [cs] / Data Structures and Algorithms [cs.DS]

Statistics [stat] / Machine Learning [stat.ML]

Complete list of metadata

https://hal.inria.fr/in2p3-00997253
Contributor : Sabine Starita <>
Submitted on : Tuesday, May 27, 2014 - 5:07:48 PM
Last modification on : Wednesday, September 16, 2020 - 5:43:24 PM

Introduction to MVA approach

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Introduction to MVA approach

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