15 citations · 26 across the 5 of their papers we have counts for
5 papers · 1 filter
Balanced Gradient Sample Retrieval for Enhanced Knowledge Retention in Proxy-based Continual Learning
Hongye Xu, Jan Wasilewski, Bartosz Krawczyk
Continual learning in deep neural networks often suffers from catastrophic forgetting, where representations for previous tasks are overwritten during subsequent training. We propo…
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…
Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning
Damien Dablain, Bartosz Krawczyk, Nitesh Chawla
Machine learning (ML) is playing an increasingly important role in rendering decisions that affect a broad range of groups in society. ML models inform decisions in criminal justic…
Efficient Augmentation for Imbalanced Deep Learning
Damien Dablain, Colin Bellinger, Bartosz Krawczyk +1
Deep learning models tend to memorize training data, which hurts their ability to generalize to under-represented classes. We empirically study a convolutional neural network's int…
Mining Drifting Data Streams on a Budget: Combining Active Learning with Self-Labeling
Łukasz Korycki, Bartosz Krawczyk
Mining data streams poses a number of challenges, including the continuous and non-stationary nature of data, the massive volume of information to be processed and constraints put…