12 citations · 13 across the 3 of their papers we have counts for
4 papers
Quantifying User Coherence: A Unified Framework for Analyzing Recommender Systems Across Domains
Michaël Soumm, Alexandre Fournier-Montgieux, Adrian Popescu +1
The performance of Recommender Systems (RS) varies significantly across users, yet the underlying reasons for this variance remain poorly understood. This paper introduces a unifie…
An Analysis of Initial Training Strategies for Exemplar-Free Class-Incremental Learning
Grégoire Petit, Michael Soumm, Eva Feillet +4
Class-Incremental Learning (CIL) aims to build classification models from data streams. At each step of the CIL process, new classes must be integrated into the model. Due to catas…
FeTrIL: Feature Translation for Exemplar-Free Class-Incremental Learning
Grégoire Petit, Adrian Popescu, Hugo Schindler +2
Exemplar-free class-incremental learning is very challenging due to the negative effect of catastrophic forgetting. A balance between stability and plasticity of the incremental pr…
PlaStIL: Plastic and Stable Memory-Free Class-Incremental Learning
Grégoire Petit, Adrian Popescu, Eden Belouadah +2
Plasticity and stability are needed in class-incremental learning in order to learn from new data while preserving past knowledge. Due to catastrophic forgetting, finding a comprom…