22 citations
- Université de MontréalCA7 papers
- Département d'InformatiqueFR3 papers
- Aarhus UniversityDK1 paper
- Canadian Institute for Advanced ResearchCA1 paper
- Centre de Génétique MoléculaireFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR1 paper
- Douglas Mental Health University InstituteCA1 paper
- Hebrew University of JerusalemIL1 paper
- Hospital Universitário da Universidade de São PauloBR1 paper
- IMT AtlantiqueFR1 paper
- Institut de Physique ThéoriqueFR1 paper
12 papers
An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam +2
In this contribution, we augment the metric learning setting by introducing a parametric pseudo-distance, trained jointly with the encoder. Several interpretations are thus drawn f…
Learning Optimal Decision Trees from Large Datasets
Florent Avellaneda
Inferring a decision tree from a given dataset is one of the classic problems in machine learning. This problem consists of buildings, from a labelled dataset, a tree such that eac…
Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks
Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel +2
Convolutional Neural Networks (CNNs) are state-of-the-art in numerous computer vision tasks such as object classification and detection. However, the large amount of parameters the…
A brain signature highly predictive of future progression to Alzheimer's dementia
Christian Dansereau, Angela Tam, AmanPreet Badhwar +4
Early prognosis of Alzheimer's dementia is hard. Mild cognitive impairment (MCI) typically precedes Alzheimer's dementia, yet only a fraction of MCI individuals will progress to de…
Improving Facial Analysis and Performance Driven Animation through Disentangling Identity and Expression
David Rim, Sina Honari, Md Kamrul Hasan +1
We present techniques for improving performance driven facial animation, emotion recognition, and facial key-point or landmark prediction using learned identity invariant represent…
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier
An important class of problems involves training deep neural networks with sparse prediction targets of very high dimension D. These occur naturally in e.g. neural language models…