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Showing 1 to 4 of 4 for “"constrained clustering"”.
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Solution of Constrained Clustering Problems through Homotopy Tracking
… fundamental machine learning problem, effective clustering under constraints. The first part of this thesis provides an empirical survey of several popular optimization algorithms, along with one approach that is cutting-edge. These algorithms are tested against deeply challenging real-world …
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Constrained Clustering for Frequency Hopping Spread Spectrum Signal Separation
… novel source separation with classic clustering algorithms can be performed. Background knowledge derived from the time domain representation of received waveforms can improve these clustering methods with the novel application of cannot-link pairwise constraints to signal separation. …
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Interactively Guiding Semi-Supervised Clustering via Attribute-based Explanations
Unsupervised image clustering is a challenging and often ill-posed problem. Existing image descriptors fail to capture the clustering criterion well, and more importantly, the criterion itself may depend on (unknown) user preferences. Semi-supervised approaches such as distance metric learning and …
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Spatial correlation tensor and query-augmented active clustering
… we propose an active metric learning method for clustering with pairwise constraints. The proposed method actively queries the label of informative instance pairs, while estimating underlying metrics by incorporating unlabeled instance pairs, which leads to a more accurate and efficient …