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cs.LG2026
Focused PU learning from imbalanced data
Elias Zavitsanos, Georgios Paliouras
We propose a new method of learning from positive and unlabeled (PU) examples in highly imbalanced datasets. Many real-world problems, such as disease gene identification, targeted…
cs.LG2024
From Primes to Paths: Enabling Fast Multi-Relational Graph Analysis
Konstantinos Bougiatiotis, Georgios Paliouras
Multi-relational networks capture intricate relationships in data and have diverse applications across fields such as biomedical, financial, and social sciences. As networks derive…