Information Bottleneck for Non Co-Occurrence Data

  title={Information Bottleneck for Non Co-Occurrence Data},
  author={Yevgeny Seldin and Noam Slonim and Naftali Tishby},
We present a general model-independent approach to the anal ysis of data in cases when these data do not appear in the form of co-occurrence of t wo variablesX,Y , but rather as a sample of values of an unknown (stochastic) fu n tionZ(X,Y ). For example, in gene expression data, the expression level Z is a function of geneX and conditionY ; or in movie ratings data the rating Z is a function of viewerX and movieY . The approach represents a consistent extension of the Info rmati n Bottleneck… CONTINUE READING


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