Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Toon Calders,Floriana Esposito,Rosa Meo Conference proceedings

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Conference proceedings 2014ers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

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0302-9743 edge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers c

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0302-9743 over the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.978-3-662-44850-2978-3-662-44851-9Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Conference proceedings 2014very in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the l

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Robust Distributed Training of Linear Classifiers Based on Divergence Minimization Principled. The goal of this distributed training is to utilize the data of all shards to obtain a well-performing linear classifier. The iterative parameter mixture (IPM) framework (Mann et al., 2009) is a state-of-the-art distributed learning framework that has a strong theoretical guarantee when the data