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cs.LG2026
Unsupervised Multi-Scale Gromov-Wasserstein Hypergraph Alignment
Lutz Oettershagen, Honglian Wang, Aristides Gionis
We study unsupervised hypergraph alignment, where the goal is to infer node correspondences between two hypergraphs using only structural information, without node features, labels…
cs.LG2026
Efficient Banzhaf-Based Data Valuation for -Nearest Neighbors Classification
Guangyi Zhang, Lutz Oettershagen, Lixu Wang +1
Data valuation, the task of quantifying the contribution of individual data points to model performance, has emerged as a fundamental challenge in machine learning. Game-theoretic…
cs.LG2026
Top-k on a Budget: Adaptive Ranking with Weak and Strong Oracles
Lutz Oettershagen
Identifying the top- items is fundamental but often prohibitive when exact valuations are expensive. We study a two-oracle setting with a fast, noisy weak oracle and a scarce, h…