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Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Ulf Brefeld,Elisa Fromont,Céline Robardet Conference proceeding

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楼主: proptosis
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Black Box Explanation by Learning Image Exemplars in the Latent Feature Spaceon method exploits the latent feature space learned through an adversarial autoencoder. The proposed method first generates exemplar images in the latent feature space and learns a decision tree classifier. Then, it selects and decodes exemplars respecting local decision rules. Finally, it visualize
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Robust Anomaly Detection in Images Using Adversarial Autoencodersage analysis. Autoencoder neural networks learn to reconstruct normal images, and hence can classify those images as anomalies, where the reconstruction error exceeds some threshold. Here we analyze a fundamental problem of this approach when the training set is contaminated with a small fraction of
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Holistic Assessment of Structure Discovery Capabilities of Clustering Algorithmsber of clusters. We suggest an efficient and holistic assessment of the structure discovery capabilities of clustering algorithms based on three criteria. We determine the robustness or stability of cluster assignments and interpret it as the confidence of the clustering algorithm in its result. Thi
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Wenjie Feng,Shenghua Liu,Xueqi Cheng général un rayon de 10 à 100 jours-lumière dans les galaxies de Seyfert et de quelques années-lumière pour les quasars lumineux. La densité électronique de ces régions (BLR pour broad line regions), est d’au moins 10. cm.. Le gaz a l’intérieur de cette région doit atteindre en général des vitesses
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