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Gradient correlation is needed to accelerate SGD with momentum
Julien Hermant
,
Marien Renaud
,
Jean-François Aujol
,
Charles Dossal
,
Aude Rondepierre
2024
Pré-publication, Document de travail
hal-04728121v1
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What is the long-run distribution of stochastic gradient descent? A large deviations analysis
Waïss Azizian
,
Franck Iutzeler
,
Jérôme Malick
,
Panayotis Mertikopoulos
ICML 2024 - 41st International Conference on Machine Learning, Jul 2024, Vienna, Austria. pp.1-70
Communication dans un congrès
hal-04629305v1
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Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemia
Erell Gachon
,
Jérémie Bigot
,
Elsa Cazelles
,
Aguirre Mimoun
,
Jean-Philippe Vial
2024
Pré-publication, Document de travail
hal-04661639v1
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Heavy Ball Momentum for Non-Strongly Convex Optimization
Jean-François Aujol
,
Charles Dossal
,
Hippolyte Labarrière
,
Aude Rondepierre
2024
Pré-publication, Document de travail
hal-04500652v1
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Study of the behaviour of Nesterov Accelerated Gradient in a non convex setting: the strongly quasar convex case
Julien Hermant
,
Jean-François Aujol
,
Charles Dossal
,
Aude Rondepierre
2024
Pré-publication, Document de travail
hal-04589853v1
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On the sequential convergence of Lloyd's algorithms
Léo Portales
,
Elsa Cazelles
,
Edouard Pauwels
2024
Pré-publication, Document de travail
hal-04593982v2
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Optimization with First Order Algorithms
Charles Dossal
,
Samuel Hurault
,
Nicolas Papadakis
2024
Pré-publication, Document de travail
hal-04755998v1
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