125 citations
- Heuristics and Diagnostics for Complex SystemsFR28 papers
- Centre National de la Recherche ScientifiqueFR23 papers
- Sorbonne UniversitéFR11 papers
- Biomécanique et BioingénierieFR4 papers
- Institut Polytechnique de BordeauxFR4 papers
- Laboratoire RobervalFR4 papers
- École Normale Supérieure Paris-SaclayFR3 papers
- Laboratoire de mathématiques appliquées de CompiègneFR3 papers
- Université de Picardie Jules VerneFR3 papers
- Université Paris Dauphine-PSLFR3 papers
- Eiffage (France)FR2 papers
- Google (United States)US2 papers
6 papers · 1 filter
Gaussian-Smoothed Sliced Probability Divergences
Mokhtar Z. Alaya, Alain Rakotomamonjy, Maxime Berar +1
Gaussian smoothed sliced Wasserstein distance has been recently introduced for comparing probability distributions, while preserving privacy on the data. It has been shown that it…
An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbers
Thierry Denoeux
We introduce a distance-based neural network model for regression, in which prediction uncertainty is quantified by a belief function on the real line. The model interprets the dis…
TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games
Gabriel Synnaeve, Nantas Nardelli, Alex Auvolat +5
We present TorchCraft, a library that enables deep learning research on Real-Time Strategy (RTS) games such as StarCraft: Brood War, by making it easier to control these games from…
Irreflexive and Hierarchical Relations as Translations
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran +2
We consider the problem of embedding entities and relations of knowledge bases in low-dimensional vector spaces. Unlike most existing approaches, which are primarily efficient for…
A Semantic Matching Energy Function for Learning with Multi-relational Data
Xavier Glorot, Antoine Bordes, Jason Weston +1
Large-scale relational learning becomes crucial for handling the huge amounts of structured data generated daily in many application domains ranging from computational biology or i…
An Efficient Approach to Sparse Linear Discriminant Analysis
Luis Francisco Sanchez Merchante, Yves Grandvalet, Gerrad Govaert
We present a novel approach to the formulation and the resolution of sparse Linear Discriminant Analysis (LDA). Our proposal, is based on penalized Optimal Scoring. It has an exact…