7 papers
Geometry-Anchored Transport Framework for Exemplar-Free Class-Incremental Learning
Hongye Xu, Bartosz Krawczyk
Exemplar-free class-incremental learning (EFCIL) requires stable decision boundaries within a shifting feature space. While maintaining class-conditional Gaussian statistics provid…
Sparsity, Superposition, and Forgetting: A Mechanistic Study of Representation Retention in Continual Learning
Jan Wasilewski, JÄdrzej Kozal, MichaÅ Woźniak +1
Continual learning (CL) systems often forget previously acquired knowledge, yet the mechanisms driving forgetting remain hard to isolate in practice because real datasets entangle…
Revisiting Prototype Rehearsal for Exemplar-Free Continual Learning: Manifold-Aware Boundary Sampling with Adaptive Class-Balanced Loss
Hongye Xu, Bartosz Krawczyk
Exemplar-free class-incremental learning (EFCIL) aims to acquire new classes over time without storing raw data. Historically, prototype rehearsal, which samples around stored clas…
Two-Way Is Better Than One: Bidirectional Alignment with Cycle Consistency for Exemplar-Free Class-Incremental Learning
Hongye Xu, Bartosz Krawczyk
Continual learning (CL) seeks models that acquire new skills without erasing prior knowledge. In exemplar-free class-incremental learning (EFCIL), this challenge is amplified becau…
Unlearning-based sliding window for continual learning under concept drift
Michal Wozniak, Marek Klonowski, Maciej Maczynski +1
Traditional machine learning assumes a stationary data distribution, yet many real-world applications operate on nonstationary streams in which the underlying concept evolves over…
What is the role of memorization in Continual Learning?
JÄdrzej Kozal, Jan Wasilewski, Alif Ashrafee +2
Memorization impacts the performance of deep learning algorithms. Prior works have studied memorization primarily in the context of generalization and privacy. This work studies th…