Experimental implementation of the paper 'Locality-Sensitive Hashing of Curves' published by A. Driemel and F. Silvestri
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Updated
Mar 25, 2019 - C
Experimental implementation of the paper 'Locality-Sensitive Hashing of Curves' published by A. Driemel and F. Silvestri
Neighbor Search and Clustering for Time-Series using Locality-sensitive hashing and Randomized Projection to Hypercube. Time series comparison is performed using Discrete Frechet or Continuous Frechet metric.
Collection of clustering algorithms for polygonal curves.
Clustering for molecular configurations
📈|Time Series - Nearest neighbor search and Clustering using LSH, Hypercube (and Lloyd's only at the clustering) algorithms with metrics: L2, Discrete and Continuous Fréchet.
Near neighbor searching and clustering using LSH
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