Probabilistic Inference for Graph Classification

Posted in Science on September 24, 2008

Probabilistic Inference for Graph Classification

Graph data is getting increasingly popular in, e.g., bioinfor- matics and text processing. A main dificulty of graph data processing lies in the intrinsic high dimensionality of graphs, namely, when a graph is represented as a binary feature vector of indicators of all possible sub- graphs, the dimensionality gets too large for usual statistical methods.

Author: Koji Tsuda, Max Planck Institute For Biological Cybernetics

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