Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Massih-Reza Amini,Stéphane Canu,Grigorios Tsoumaka Conference p

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Truly Unordered Probabilistic Rule Sets for?Multi-class Classificatione sets. We next develop a two-phase heuristic algorithm that learns rule sets by carefully growing rules. An important innovation is that we use a surrogate score to take the global potential of the rule set into account when learning a local rule..Finally, we empirically demonstrate that, compared

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Summarizing Data Structures with Gaussian Process and Robust Neighborhood Preservation-posterior distribution based on low-rank matrix approximation, which allows LolaGP to handle larger datasets than the conventional GP-LVM extensions. Our contribution is to preserve both the global and local structures in the derivation of the latent variables using the robust neighborhood graph an

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Bounding the?Family-Wise Error Rate in?Local Causal Discovery Using Rademacher Averagesion on simulated data shows that our algorithm properly controls for the FWER, while widely used algorithms do not provide guarantees on false discoveries even when correcting for multiple-hypothesis testing. Our experiments also show that our algorithm identifies meaningful relations in real-world

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Conference proceedings 2023rative models; computer vision; meta-learning, neural architecture search; ..Part IV:. Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; ...Part V:. Supervised learning; probabilistic inferenc

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0302-9743 rning; bandits and online learning; active and semi-supervised learning; private and federated learning; ...Part V:. Supervised learning; probabilistic inferenc978-3-031-26418-4978-3-031-26419-1Series ISSN 0302-9743 Series E-ISSN 1611-3349

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