Titlebook: Machine Learning and Knowledge Discovery in Databases, Part II; European Conference, Dimitrios Gunopulos,Thomas Hofmann,Michalis Vazirg Con

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Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithmsersion problem; (b) for practical applications, we developed ., a fast algorithm that yields 2× speedup, equal or higher accuracy than BP, and is guaranteed to converge. We demonstrate these benefits using synthetic and real datasets, including YahooWeb, one of the largest graphs ever studied with BP.

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Toward a Fair Review-Management Systemg force. Therefore, keeping the reviewers satisfied and motivated to continue submitting high-quality content is essential. In this paper, we propose a system that helps potential buyers by focusing on high-quality and informative reviews, while keeping reviewers content and motivated.

北極人

GUILT

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Machine Learning and Knowledge Discovery in Databases, Part II978-3-642-23783-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Dimitrios Gunopulos,Thomas Hofmann,Michalis VazirgFast-track conference proceedings.State-of-the-art research.Up-to-date results

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