By Pedro Latorre Carmona, J. Salvador Sánchez, Ana L.N. Fred
On order equivalences among distance and similarity measures on sequences and trees.- Scalable Corpus Annotation through Graph building and Label Propagation.- Computing the reeb graph for triangle meshes with lively contours.- effective Computation of Voronoi friends in line with Polytope seek in trend Recognition.- Estimation of the typical oscillation for section Locked Matrix Factorization.- ASSET: Approximate Stochastic Subgradient Estimation education for aid Vector Machines.- Pitch-sensitive parts emerge from Hierarchical Sparse Coding of typical Sounds.- Generative Embeddings in line with Rican combinations: program to KernelBased Discriminative class of Magnetic Resonance Images.-Single-Frame sign restoration utilizing a Similarity-Prior according to Pearson variety VII MRF.- monitoring options of time various linear inverse problems.- Stacked Conditional Random Fields Exploiting Structural Consistencies.- Segmentation of Vessel Geometries from scientific photographs utilizing GPF Deformable Model.- strong Deformable version for Segmenting the Left Ventricle in 3D volumes of Ultrasound Data.- set of rules to take care of linear point in 3D point Set Topology Optimization.- facial features reputation utilizing Log-Euclidean statistical form types
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51(1), 69–82 (2000) 5. : Scaling up all pairs similarity search. In: Proceedings of the 16th International Conference on World Wide Web, pp. 131–140. ACM, New York (2007) 6. : Regularization and semi-supervised learning on large graphs. In: Learning Theory, pp. 624–638. Springer, Berlin (2004) 7. : Proximity graphs for clustering and manifold learning. In: Advances in Neural Information Processing Systems 17. NIPS-17, MIT Press (2004) 8. : Random spanning trees and the prediction of weighted graphs.
Efficient k-nearest neighbor graph construction for generic similarity measures. In: Proceedings of the 20th International Conference on World Wide Web, pp. 577–586. ACM, New York (2011) 14. : NOAM: news outlets analysis and monitoring system. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data, pp. 1275–1278. ACM, New York (2011) 15. : Similarity search in high dimensions via hashing. In: Proceedings of the 25th International Conference on Very Large Data Bases, pp.
Therefore, any improvement in the computation of the Voronoi tesselation will imply a reduction in the computational cost of any procedure that can be obtained from this tesselation as the k-NN. In this approach of using spatial information provided by Dlaunay/Vornoy methods clustering method [21] is an agglomerative clustering algorithm which access density information by constructing a Voronoi diagram for the input samples. The Voronoi tessellation procedure uses the metric distance to define the boundary planes between regions or cells.