Constrained clustering
On the Use of Ontology as a priori Knowledge into Constrained Clustering
... Figure 3 shows the results of applying our approach to one of the images used in the experiments. For a better understanding, Figure 3 should be analyzed in color mode. Figure 3.a represents the raw image in true colors; ...
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Constrained Clustering: Current and New Trends
... Incremental Constrained Clustering Many constrained clustering methods require that the complete set of constraints be given before running the ...document clustering, in which ten ...
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Deep constrained clustering applied to satellite image time series
... context, constrained clustering, which is a class of semi-supervised learning algo- rithms, is an alternative and offers a good trade-off of ...deep clustering ap- proaches to process satellite image ...
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Adaptive sampling using fleets of underwater gliders in the presence of fixed buoys using a constrained clustering algorithm
... Index Terms—adaptive sampling, underwater gliders, clustering algorithms, fuzzy C-means. I. I NTRODUCTION The use of fleets of underwater gliders to sample the ocean has been proven to be an appealing alternative ...
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Constrained Distance Based K-Means Clustering for Satellite Image Time-Series
... unsupervised clustering in applications that are still not for- malised ...descriptions). Constrained clustering (alias semi-supervised clustering) is the process of introducing background ...
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Constrained variable clustering and the best basis problem in functional data analysis
... A different line of thoughts is followed in the present paper: the goal is to extract features that are easy to interpret in terms of the original variables. This is done by approximating the original functions by ...
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Adjacency-constrained hierarchical clustering of a band similarity matrix with application to Genomics
... adjacency- constrained clustering algorithm with quasi-linear complexity (namely, O(ph) in space and O(p(h + log(p))) in time) under this assumption, and to demonstrate its relevance for genomic ...
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Constrained Density Functional Theory
... the constrained Fock matrices are then applied to the historic core Fock matrices to yield an extrapolated core Fock matrix; the microiterations to determine the constraint potentials add a constraint potential to ...
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Toward Constrained Semantic WoT
... On the other hand, the Linked Data initiative 6 encourages entities to publish structured data enriched with semantics and relies on the notion of hypermedia link to map them together. Lanthaler et al. point out that ...
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Co-Clustering Network-Constrained Trajectory Data
... trajectory clustering focused on the case of moving ob- jects evolving freely in the euclidean space [Kalnis et ...the clustering process. Clustering network-constrained tra- jectories gained ...
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Constrained Palette-Space Exploration
... Palette optimization for Color Vision Deficiencies (CVD) rather focuses on finding a balance between aesthetic and accessibility con- straints. Such problems are usually over-constrained, and enable the use of ...
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Size-Constrained Tree Decompositions
... treewidth graphs, efficient (i.e., practical) algorithms exist to compute tree-decompositions with optimal width. More- over, in such case, the time-complexity of above-mentioned dynamic programming algorithms becomes ...
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Power Spectral Clustering
... 34. Song, Y., Chen, W.Y., Bai, H., Lin, C.J., Chang, E.: Paral- lel spectral clustering. Machine Learning and Knowledge Discovery in Databases pp. 374–389 (2008) 35. Turaga, S.C., Briggman, K.L., Helmstaedter, M., ...
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Robust Bregman Clustering
... to clustering with other Bregman divergences (including trimmed k-means [ 16 ]), trimmed k-median [ 9 ], tclust [ 22 ], and density/distance functions-based clustering schemes such as a robustified version ...
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Constrained Markov Decision Processes
... archive for the deposit and dissemination of sci- entific research documents, whether they are pub- L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau ...
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Algorithms and hardness results for the jump number problem, the joint replenishment problem, and the optimal clustering of frequency-constrained maintenance jobs
... These algorithms allow us to extend the classes of partial orders for which the jump number can be computed in polynomial time, as well as to provide a significa[r] ...
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Block-constrained compressed sensing
... 6 Conclusion In this chapter, we have focused on constrained acquisition by blocks of measurements. Sampling schemes are constructed by drawing blocks of measurements from a given dic- tionary of blocks according ...
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Constrained Sparse Texture Synthesis
... This paper presents a novel texture synthesis algorithm that performs a sparse expansion of the patches of the image in a dictionary learned from an input exemplar.. The synthesized text[r] ...
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Essays on capacity-constrained pricing
... Related literature In order to position the contributions of this dissertation in the literature, the following section provides a short, non-exhaustive survey of the existing models of capacity-constrained ...
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Synthesis of constrained nucleosides
... 78 first macrocyclic oligonucleotides joined by phosphate ester bonds were developed by Nielsen 182-187 who used RCM to build the macrocycle (Figure 25). The resulting di- and tri- nucleotides had constrained ...
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