collaborators

5 papers

cs.DB2026

Incremental Delta-Shapley: A Standalone Runtime for Predicate Attribution on Sliding Windows

Pouya Khani, Ira Assent

Continuous aggregate queries over sliding windows are common in real-time analytics, but most systems report \emph{what} an aggregate is doing without attributing \emph{which} pred…

cs.DB2026

Closed-Form Predicate-Level Shapley Attribution for Sliding-Window Aggregates

Pouya Khani, Ira Assent

Streaming engines report sliding-window aggregates in real time, but they do not explain \emph{why} an aggregate takes its current value. A natural target is the Shapley value from…

cs.LG2026

ExDBSCAN: Explaining DBSCAN with Counterfactual Reasoning -- Additional Material

Pernille Matthews, Lena Krieger, Tommaso Amico +3

Clustering is an unsupervised technique for grouping data points by similarity. While explainability methods exist for supervised machine learning, they are not directly applicable…

cs.LG2025

Internal Evaluation of Density-Based Clusterings with Noise

Anna Beer, Lena Krieger, Pascal Weber +3

Being able to evaluate the quality of a clustering result even in the absence of ground truth cluster labels is fundamental for research in data mining. However, most cluster valid…

cs.LG2025

Ultrametric Cluster Hierarchies: I Want 'em All!

Andrew Draganov, Pascal Weber, Rasmus Skibdahl Melanchton Jørgensen +3

Hierarchical clustering is a powerful tool for exploratory data analysis, organizing data into a tree of clusterings from which a partition can be chosen. This paper generalizes th…