516 citations · 751 across the 16 of their papers we have counts for
19 papers
Smoothness-Based Derandomization of PAC-Bayes Bounds
Alexandre Lemire Paquin, Brahim Chaib-Draa, Philippe Giguère
We study PAC-Bayes derandomization for smooth loss functions. Our goal is to obtain generalization bounds that hold with high probability for deterministic predictors by exploiting…
Symmetrization of Loss Functions for Robust Training of Neural Networks in the Presence of Noisy Labels
Alexandre Lemire Paquin, Brahim Chaib-Draa, Philippe Giguère
Labeling a training set is often expensive and susceptible to errors, making the design of robust loss functions for label noise an important problem. The symmetry condition provid…
BoQ: A Place is Worth a Bag of Learnable Queries
Amar Ali-Bey, Brahim Chaib-draa, Philippe Giguère
In visual place recognition, accurately identifying and matching images of locations under varying environmental conditions and viewpoints remains a significant challenge. In this…
MixVPR: Feature Mixing for Visual Place Recognition
Amar Ali-bey, Brahim Chaib-draa, Philippe Giguère
Visual Place Recognition (VPR) is a crucial part of mobile robotics and autonomous driving as well as other computer vision tasks. It refers to the process of identifying a place d…
Dynamic Y-KD: A Hybrid Approach to Continual Instance Segmentation
Mathieu Pagé-Fortin, Brahim Chaib-draa
Despite the success of deep learning models on instance segmentation, current methods still suffer from catastrophic forgetting in continual learning scenarios. In this paper, our…
Global Proxy-based Hard Mining for Visual Place Recognition
Amar Ali-bey, Brahim Chaib-draa, Philippe Giguère
Learning deep representations for visual place recognition is commonly performed using pairwise or triple loss functions that highly depend on the hardness of the examples sampled…