5 papers
Sparsity, Superposition, and Forgetting: A Mechanistic Study of Representation Retention in Continual Learning
Jan Wasilewski, Jędrzej Kozal, Michał 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…
Holistic Continual Learning under Concept Drift with Adaptive Memory Realignment
Alif Ashrafee, Jedrzej Kozal, Michal Wozniak +1
Traditional continual learning methods prioritize knowledge retention and focus primarily on mitigating catastrophic forgetting, implicitly assuming that the data distribution of p…
Continual Learning with Weight Interpolation
Jędrzej Kozal, Jan Wasilewski, Bartosz Krawczyk +1
Continual learning poses a fundamental challenge for modern machine learning systems, requiring models to adapt to new tasks while retaining knowledge from previous ones. Addressin…
A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanism
Radek Svoboda, Sebastian Basterrech, Jedrzej Kozal +2
Forecasting natural gas consumption, considering seasonality and trends, is crucial in planning its supply and consumption and optimizing the cost of obtaining it, mainly by indust…
Combining Self-labeling with Selective Sampling
Jędrzej Kozal, Michał Woźniak
Since data is the fuel that drives machine learning models, and access to labeled data is generally expensive, semi-supervised methods are constantly popular. They enable the acqui…