275 citations · 551 across the 32 of their papers we have counts for
39 papers
Rethinking Tabular Foundation Models On Data Streams
Nilesh Verma, Daniel Nowak-Assis, Afonso Lourenço +4
Tabular foundation models (TFMs) outperform established machine learning models on tabular benchmarks through in-context learning. Building on this success, interest is growing in…
TuiML: Machine Learning for AI Agents
Nilesh Verma, Nick Lim, Albert Bifet +1
Machine-learning libraries such as Weka and scikit-learn were designed for human programmers. Language-model agents now use these same libraries by recalling APIs from memory and w…
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…