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A clustering technique for the identification of Piecewise Affine Systems

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Kernelized Infomax Clustering

We propose a simple information-theoretic clustering approach based on maximizing the mutual information

I(\sfx,y)

between the unknown cluster labels

y

and the training patterns

\sfx

with respect to parameters of specifically constrained encoding dis ...

IDIAP2005

A clustering technique for the identification of Piecewise Affine Systems

Graph Chatbot

Chattez avec Graph Search

Learning Cluster Type and Dissimilarity Metric for Each Cluster Using a Set of Possible Cluster Types

Likelihood estimation of the extremal index

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Kernelized Infomax Clustering

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Discovering Coherent Biclusters from Gene Expression Data Using Zero-Suppressed Binary Decision Diagrams

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Effect of Recognition Errors on Text Clustering

A clustering technique for the identification of piecewise affine and hybrid systems

Kernelized Infomax Clustering

Discovering Coherent Biclusters from Gene Expression Data Using Zero-Suppressed Binary Decision Diagrams

Multi-layer hierarchical clustering of pedestrian trajectories for automatic counting of people in video sequences

Effect of Recognition Errors on Text Clustering

Counting pedestrians in video sequences using trajectory clustering

A clustering technique for the identification of piecewise affine and hybrid systems

Noisy Text Clustering

Making Retrieval Faster Through Document Clustering

Learning Cluster Type and Dissimilarity Metric for Each Cluster Using a Set of Possible Cluster Types

Likelihood estimation of the extremal index