Displaying similar documents to “Coalgebraic decision theory”

On A-Trees

Đuro Kurepa (1968)

Publications de l'Institut Mathématique

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Classification of Paintings by Artist, Movement, and Indoor Setting Using MPEG-7 Descriptor Features

Welch, Charles (2014)

Serdica Journal of Computing

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ACM Computing Classification System (1998): I.4.9, I.4.10. Image classification is an essential problem for content based image retrieval and image processing. Visual properties can be extracted from images in the form of MPEG-7 descriptors. Statistical methods can use these properties as features and be used to derive an effective method of classifying images by evaluating a minimal number of properties used in the MPEG-7 descriptor. Classification by artist, artistic movement,...

Completely Independent Spanning Trees in (Partial) k-Trees

Masayoshi Matsushita, Yota Otachi, Toru Araki (2015)

Discussiones Mathematicae Graph Theory

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Two spanning trees T1 and T2 of a graph G are completely independent if, for any two vertices u and v, the paths from u to v in T1 and T2 are internally disjoint. For a graph G, we denote the maximum number of pairwise completely independent spanning trees by cist(G). In this paper, we consider cist(G) when G is a partial k-tree. First we show that [k/2] ≤ cist(G) ≤ k − 1 for any k-tree G. Then we show that for any p ∈ {[k/2], . . . , k − 1}, there exist infinitely many k-trees G such...

On a matching distance between rooted phylogenetic trees

Damian Bogdanowicz, Krzysztof Giaro (2013)

International Journal of Applied Mathematics and Computer Science

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The Robinson-Foulds (RF) distance is the most popular method of evaluating the dissimilarity between phylogenetic trees. In this paper, we define and explore in detail properties of the Matching Cluster (MC) distance, which can be regarded as a refinement of the RF metric for rooted trees. Similarly to RF, MC operates on clusters of compared trees, but the distance evaluation is more complex. Using the graph theoretic approach based on a minimum-weight perfect matching in bipartite graphs,...

A model of decision with linguistic knowledge.

María Teresa Lamata Jiménez (1994)

Mathware and Soft Computing

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The aim of this paper is to develop a new aggregating method for the decision problem in which the possible values of rewards are known in linguistic terms. We show new operators for solving this problem, as well as the way in which OWA operators provide us with an adequate framework for representing the optimism degree of the decision maker in case we have no information about the real state.