55 citations
- Laboratoire de Recherche en InformatiqueFR7 papers
- Université Paris-SudFR5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Université Paris-SaclayFR4 papers
- Institut national de recherche en sciences et technologies du numériqueFR3 papers
- Meta (United States)US3 papers
- ChaLearn2 papers
- National Institute of Astrophysics, Optics and ElectronicsMX2 papers
- Sorbonne UniversitéFR2 papers
- Tel Aviv UniversityIL2 papers
- 4Thparadigm (China)1 paper
- Apple (United States)US1 paper
12 papers
Distribution-Based Invariant Deep Networks for Learning Meta-Features
Gwendoline De Bie, Herilalaina Rakotoarison, Gabriel Peyré +1
Recent advances in deep learning from probability distributions successfully achieve classification or regression from distribution samples, thus invariant under permutation of the…
An Equivalence between Bayesian Priors and Penalties in Variational Inference
Pierre Wolinski, Guillaume Charpiat, Yann Ollivier
In machine learning, it is common to optimize the parameters of a probabilistic model, modulated by an ad hoc regularization term that penalizes some values of the parameters. Regu…
LEAP nets for power grid perturbations
Benjamin Donnot, Balthazar Donon, Isabelle Guyon +4
We propose a novel neural network embedding approach to model power transmission grids, in which high voltage lines are disconnected and reconnected with one-another from time to t…
Towards AutoML in the presence of Drift: first results
Jorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales +5
Research progress in AutoML has lead to state of the art solutions that can cope quite wellwith supervised learning task, e.g., classification with AutoSklearn. However, so far the…
Inverse problems for structured datasets using parallel TAP equations and RBM
Aurélien Decelle, Sungmin Hwang, Jacopo Rocchi +1
We propose an efficient algorithm to solve inverse problems in the presence of binary clustered datasets. We consider the paradigmatic Hopfield model in a teacher student scenario,…
Learning a Local Symmetry with Neural-Networks
Aurélien Decelle, Victor Martin-Mayor, Beatriz Seoane
We explore the capacity of neural networks to detect a symmetry with complex local and non-local patterns : the gauge symmetry Z 2 . This symmetry is present in physical problems f…