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Fast vector quantization with topology learning
Fast vector quantization with topology learning
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机译:通过拓扑学习进行快速矢量量化
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摘要
A new process called a vector approximation graph (VA-graph) leverages a tree based vector quantizer to quickly learn the topological structure of the data. It then uses the learned topology to enhance the performance of the vector quantizer. A method for analyzing data comprises receiving data, partitioning the data and generating a tree based on the partitions, learning a topology of a distribution of the data, and finding a best matching unit in the data using the learned topology.
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