Science of Machine Learning

Find a good number of salient patterns in a matrix

- Infinite plaid models for infinite bi-clustering -

Abstract

Our goal is to find salient bi-clusters from a given relational data matrix automatically. Salient bi-clusters are sub-matrices that have distinct values from other entries of the data matrix. Such bi-clusters often corresponds to informative subsets of the data; e.g. “good customer groups with best-selling items for them”, and “specific gene clusters that are reactive for a specific treatment/chemicals” .
Conventionally, bi-clustering requires us to specify the number of bi-clusters to be extracted before the analysis. Howeverit is generally difficult to know the number of bi-clusters before conducting an actual analysis.
Our proposed model enables us to forget about this specification of the number of bi-clusters. The model automatically infer an appropriate number of bi-clusters (up to infinite!) for the given data matrix, and performs effective bi-clustering. This model will help users to conduct “easy-to-go” bi-clustering for several situations.

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Poster


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Presenters

Katsuhiko Ishiguro
Katsuhiko Ishiguro
Innovative Communication Laboratory
Akisato Kimura
Akisato Kimura
Media Information Laboratory
Kou Takeuchi
Kou Takeuchi
Ueda Research Laboratory
Takuma Otsuka
Takuma Otsuka
Innovative Communication Laboratory