1.9k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Georges Kaddoum6 profiles32 · h 49
- Ismail Ben Ayed3 profiles30 · h 52
- P. Giard28 · h 18
- R. Sabourin28 · h 58
- J. Dolz26 · h 43
- Christian Desrosiers2 profiles24 · h 37
- Eric Granger2 profiles20 · h 32
- F. Gagnon17 · h 32
- Rafael M. O. Cruz17 · h 22
- M. Cheriet15 · h 51
- C. Thibeault14 · h 21
- Marco Pedersoli3 profiles14 · h 20
- Université du Québec à MontréalCA58 papers
- McGill UniversityCA38 papers
- Polytechnique MontréalCA25 papers
- Universidade Federal de PernambucoBR17 papers
- Université du QuébecCA14 papers
- Université de MontréalCA13 papers
- Centre National de la Recherche ScientifiqueFR11 papers
- University of OttawaCA11 papers
- Carleton UniversityCA10 papers
- Guilin University of Electronic TechnologyCN10 papers
- Concordia UniversityCA9 papers
- École Polytechnique Fédérale de LausanneCH9 papers
5 papers · 2 filters
IncA-DES: An incremental and adaptive dynamic ensemble selection approach using online K-d tree neighborhood search for data streams with concept drift
Eduardo V. L. Barboza, Paulo R. Lisboa de Almeida, Alceu de Souza Britto +2
Data streams pose challenges not usually encountered in batch-based ML. One of them is concept drift, which is characterized by the change in data distribution over time. Among man…
Resampling strategies for imbalanced regression: a survey and empirical analysis
Juscimara G. Avelino, George D. C. Cavalcanti, Rafael M. O. Cruz
Imbalanced problems can arise in different real-world situations, and to address this, certain strategies in the form of resampling or balancing algorithms are proposed. This issue…
Imbalanced Regression Pipeline Recommendation
Juscimara G. Avelino, George D. C. Cavalcanti, Rafael M. O. Cruz
Imbalanced problems are prevalent in various real-world scenarios and are extensively explored in classification tasks. However, they also present challenges for regression tasks d…
FAA-CLIP: Federated Adversarial Adaptation of CLIP
Yihang Wu, Ahmad Chaddad, Christian Desrosiers +2
Despite the remarkable performance of vision language models (VLMs) such as Contrastive Language Image Pre-training (CLIP), the large size of these models is a considerable obstacl…
Simulations of Common Unsupervised Domain Adaptation Algorithms for Image Classification
Ahmad Chaddad, Yihang Wu, Yuchen Jiang +2
Traditional machine learning assumes that training and test sets are derived from the same distribution; however, this assumption does not always hold in practical applications. Th…