10 citations · 11 across the 3 of their papers we have counts for
6 papers
Learning from missing data with the Latent Block Model
Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet
Missing data can be informative. Ignoring this information can lead to misleading conclusions when the data model does not allow information to be extracted from the missing data.…
Driving among Flatmobiles: Bird-Eye-View occupancy grids from a monocular camera for holistic trajectory planning
Abdelhak Loukkal, Yves Grandvalet, Tom Drummond +1
Camera-based end-to-end driving neural networks bring the promise of a low-cost system that maps camera images to driving control commands. These networks are appealing because the…
Representation Transfer by Optimal Transport
Xuhong Li, Yves Grandvalet, Rémi Flamary +2
Learning generic representations with deep networks requires massive training samples and significant computer resources. To learn a new specific task, an important issue is to tra…
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Xuhong Li, Yves Grandvalet, Franck Davoine
In inductive transfer learning, fine-tuning pre-trained convolutional networks substantially outperforms training from scratch. When using fine-tuning, the underlying assumption is…
Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases
Alberto Garcia-Duran, Antoine Bordes, Nicolas Usunier +1
This paper tackles the problem of endogenous link prediction for Knowledge Base completion. Knowledge Bases can be represented as directed graphs whose nodes correspond to entities…
Beyond Support in Two-Stage Variable Selection
Jean-Michel Bécu, Yves Grandvalet, Christophe Ambroise +1
Numerous variable selection methods rely on a two-stage procedure, where a sparsity-inducing penalty is used in the first stage to predict the support, which is then conveyed to th…