3 papers
cs.LG2026
One Loop, Two Gains: Can Active Learning win the Lottery for Free?
Benedikt Tscheschner, Eduardo Veas, Marc Masana
The lottery ticket hypothesis posits the existence of winning tickets: sparse subnetworks that, when trained in isolation from their original initialization, match the accuracy of…
cs.LG2025
Incremental Learning with Repetition via Pseudo-Feature Projection
Benedikt Tscheschner, Eduardo Veas, Marc Masana
Incremental Learning scenarios do not always represent real-world inference use-cases, which tend to have less strict task boundaries, and exhibit repetition of common classes and…
cs.LG2024
Continual Learning in the Presence of Repetition
Hamed Hemati, Lorenzo Pellegrini, Xiaotian Duan +11
Continual learning (CL) provides a framework for training models in ever-evolving environments. Although re-occurrence of previously seen objects or tasks is common in real-world p…