Avishay Friedman

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Pairwise clustering methods partition a dataset using pairwise similarity between data-points. The pairwise similarity matrix can be used to define a Markov random walk on the data points. This view forms a probabilistic interpretation of spectral clustering methods. We utilize this probabilistic model to define a novel clustering cost function that is(More)
In this paper we develop an information-theoretic approach for pairwise clustering. The Laplacian of the pairwise similarity matrix can be used to define a Markov random walk on the data points. This view forms a probabilistic interpretation of spectral clustering methods. We utilize this probabilistic model to define a novel clustering cost function that(More)
Application of a unified classical approach to the modeling and analysis of both deductive and defeasible reasoning developed by the authors on the basis of n-tuple algebra is demonstrated. A method of analysis of defeasible reasoning transferring the “non-classical” component to the semantics and allowing carrying out logical analysis without violating the(More)
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