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cs.LG2023
Weighted Ensemble Models Are Strong Continual Learners
Imad Eddine Marouf, Subhankar Roy, Enzo Tartaglione +1
In this work, we study the problem of continual learning (CL) where the goal is to learn a model on a sequence of tasks, such that the data from the previous tasks becomes unavaila…
cs.CV2023
Mini but Mighty: Finetuning ViTs with Mini Adapters
Imad Eddine Marouf, Enzo Tartaglione, Stéphane Lathuilière
Vision Transformers (ViTs) have become one of the dominant architectures in computer vision, and pre-trained ViT models are commonly adapted to new tasks via fine-tuning. Recent wo…
cs.CV2023
Enhancing Plasticity for First Session Adaptation Continual Learning
Imad Eddine Marouf, Subhankar Roy, Stéphane Lathuilière +1
The integration of large pre-trained models (PTMs) into Class-Incremental Learning (CIL) has facilitated the development of computationally efficient strategies such as First-Sessi…