275 citations · 302 across the 16 of their papers we have counts for
17 papers · 1 filter
Rashomon Alignment
Moisés Santos, Peter van der Putten, Bernhard Pfahringer +1
We propose Rashomon Alignment (RA), a new measure to assess functional similarity between two models. Existing functional similarity measures are distributional, quantifying differ…
A Framework for Evaluating and Benchmarking Concept Drift Detection Methods
Vitor Cerqueira, Heitor Murilo Gomes, Marco Heyden +2
Data stream mining is fundamentally challenged by concept drift, where distributional changes can degrade model performance. Despite the proliferation of drift detection methods, p…
Policy Gradient with Adaptive Entropy Annealing for Continual Fine-Tuning
Yaqian Zhang, Bernhard Pfahringer, Eibe Frank +1
Despite their success, large pretrained vision models remain vulnerable to catastrophic forgetting when adapted to new tasks in class-incremental settings. Parameter-efficient fine…
ARES: Anomaly Recognition Model For Edge Streams
Simone Mungari, Albert Bifet, Giuseppe Manco +1
Many real-world scenarios involving streaming information can be represented as temporal graphs, where data flows through dynamic changes in edges over time. Anomaly detection in t…
Detecting Domain Shifts in Myoelectric Activations: Challenges and Opportunities in Stream Learning
Yibin Sun, Nick Lim, Guilherme Weigert Cassales +4
Detecting domain shifts in myoelectric activations poses a significant challenge due to the inherent non-stationarity of electromyography (EMG) signals. This paper explores the det…
Online Isolation Forest
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer +2
The anomaly detection literature is abundant with offline methods, which require repeated access to data in memory, and impose impractical assumptions when applied to a streaming c…