Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Michele Berlingerio,Francesco Bonchi,Georgiana Ifr Conference p

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Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Boundsvide a flexible and powerful framework for probabilistic inference, their performance is highly dependent on the choice of kernel and regularization hyperparameters. Nevertheless, current hyperparameter tuning methods predominantly rely on expensive cross validation or heuristics that is not optimiz

鞠躬

Deep Learning Architecture Search by Neuro-Cell-Based Evolution with Function-Preserving Mutationst knowledge. We propose a novel neuro-evolutionary technique to solve this problem without human interference. Our method assumes that a convolutional neural network architecture is a sequence of neuro-cells and keeps mutating them using function-preserving operations. This novel combination of appr

Stable-Angina

VC-Dimension Based Generalization Bounds for Relational Learningll fragment from some social network). In this paper we are particularly concerned with scenarios in which we can assume that (i) the domain elements appearing in the given sample have been uniformly sampled without replacement from the (unknown) full domain and (ii) the sample is complete for these

Anticoagulants

Social-Affiliation Networks: Patterns and the , Modelelf-similarity, to . generate graphs obeying the observed patterns. Experiments show that: (i) the discovered rules are useful in detecting deviations as anomalies and (ii) . is fast and scales linearly with network size, producing graphs with millions of edges and attributes in only a few seconds. Code related to this paper is available at: ..

GUILT

: Modeling the Co-evolution of Opinions and Network Connectionstence or dissolution of social ties. Using a unique real-world network dataset including periodic user surveys, we show that . performs with high accuracy, while outperforming the baseline approaches. Code related to this paper is available at: . and Data related to this paper is available at: ..

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GROSS

Fast and Provably Effective Multi-view Classification with Landmark-Based SVMsing-view scenario by only reconstructing the similarities to the landmarks. Empirical results, both in complete and missing view settings, highlight the superior performances of our method, in terms of accuracy and execution time, w.r.t. state of the art techniques. Code related to this paper is available at: ..

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0302-9743 ledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018.?. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track.?.The contribut