244 citations · 250 across the 10 of their papers we have counts for
7 papers · 1 filter
Model-Agnostic Few-Shot Open-Set Recognition
Malik Boudiaf, Etienne Bennequin, Myriam Tami +4
We tackle the Few-Shot Open-Set Recognition (FSOSR) problem, i.e. classifying instances among a set of classes for which we only have few labeled samples, while simultaneously dete…
Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query Shift
Etienne Bennequin, Victor Bouvier, Myriam Tami +2
Few-Shot Learning (FSL) algorithms have made substantial progress in learning novel concepts with just a handful of labelled data. To classify query instances from novel classes en…
Stochastic Adversarial Gradient Embedding for Active Domain Adaptation
Victor Bouvier, Philippe Very, Clément Chastagnol +2
Unsupervised Domain Adaptation (UDA) aims to bridge the gap between a source domain, where labelled data are available, and a target domain only represented with unlabelled data. I…
An Overview of Deep Semi-Supervised Learning
Yassine Ouali, Céline Hudelot, Myriam Tami
Deep neural networks demonstrated their ability to provide remarkable performances on a wide range of supervised learning tasks (e.g., image classification) when trained on extensi…
Target Consistency for Domain Adaptation: when Robustness meets Transferability
Yassine Ouali, Victor Bouvier, Myriam Tami +1
Learning Invariant Representations has been successfully applied for reconciling a source and a target domain for Unsupervised Domain Adaptation. By investigating the robustness of…
Robust Domain Adaptation: Representations, Weights and Inductive Bias
Victor Bouvier, Philippe Very, Clément Chastagnol +2
Unsupervised Domain Adaptation (UDA) has attracted a lot of attention in the last ten years. The emergence of Domain Invariant Representations (IR) has improved drastically the tra…
Uncertain Trees: Dealing with Uncertain Inputs in Regression Trees
Myriam Tami, Marianne Clausel, Emilie Devijver +4
Tree-based ensemble methods, as Random Forests and Gradient Boosted Trees, have been successfully used for regression in many applications and research studies. Furthermore, these…