36 citations · 126 across the 16 of their papers we have counts for
Showing 2023 · cs.LGShow all
2 papers · 2 filters
cs.LG2023
From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning
Kamil Faber, Dominik Zurek, Marcin Pietron +3
Continual learning (CL) is one of the most promising trends in recent machine learning research. Its goal is to go beyond classical assumptions in machine learning and develop mode…
cs.LG2023★ 36 cited
Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski +1
Anomaly detection is of paramount importance in many real-world domains, characterized by evolving behavior. Lifelong learning represents an emerging trend, answering the need for…