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Gains and Losses are Fundamentally Different in Regret Minimization: The Sparse Case

Vianney Perchet 1, 2, 3 Joon Kwon 4
1 SIERRA - Statistical Machine Learning and Parsimony
DI-ENS - Département d'informatique de l'École normale supérieure, ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
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Preprints, Working Papers, ...
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https://hal.archives-ouvertes.fr/hal-01265075
Contributor : Vianney Perchet <>
Submitted on : Saturday, January 30, 2016 - 6:47:24 PM
Last modification on : Monday, May 25, 2020 - 3:14:17 PM

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  • HAL Id : hal-01265075, version 1
  • ARXIV : 1511.08405

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Vianney Perchet, Joon Kwon. Gains and Losses are Fundamentally Different in Regret Minimization: The Sparse Case . 2015. ⟨hal-01265075⟩

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