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no code implementations • 15 Jun 2020 • Mieczysław A. Kłopotek

It is demonstrated that the p-d-separation within the pog is equivalent to d-separation in all derived dags.

no code implementations • 25 May 2020 • Mieczysław A. Kłopotek

It applies general conditional belief functions.

no code implementations • 28 Sep 2019 • Mieczysław A. Kłopotek

It is proven, by example, that the version of $k$-means with random initialization does not have the property \emph{probabilistic $k$-richness}.

no code implementations • 26 Sep 2019 • Mieczysław A. Kłopotek, Sławomir T. Wierzchoń

Valuation-Based~System can represent knowledge in different domains including probability theory, Dempster-Shafer theory and possibility theory.

no code implementations • 14 Dec 2018 • Andrzej Matuszewski, Mieczysław A. Kłopotek

One important obstacle in applying Dempster-Shafer Theory (DST) is its relationship to frequencies.

no code implementations • 7 Dec 2018 • Mieczysław A. Kłopotek, Sławomir T. Wierzchoń

Mathematical Theory of Evidence (MTE), a foundation for reasoning under partial ignorance, is blamed to leave frequencies outside (or aside of) its framework.

no code implementations • 30 Nov 2018 • Mieczysław A. Kłopotek

The paper gives an overview of the problems and methods of recovery of structure and motion parameters of rigid bodies from multiframes.

no code implementations • 6 Jun 2018 • Mieczysław A. Kłopotek

A number of algorithms exists for decomposition of probabilistic joint belief distribution into a bayesian (belief) network from data.

no code implementations • 30 May 2018 • Mieczysław A. Kłopotek

Fundamental reason for failure of this algorithm is the temporary introduction of non-real links between nodes of the network with the intention of later removal.

no code implementations • 13 Jul 2017 • Mieczysław A. Kłopotek

Hidden variables are well known sources of disturbance when recovering belief networks from data based only on measurable variables.

no code implementations • 13 Jul 2017 • Mieczysław A. Kłopotek

It excludes especially so-called probabilistic belief functions.

no code implementations • 12 Jul 2017 • Mieczysław A. Kłopotek

On the other hand, though Shenoy and Shafer's hypergraphs can explicitly represent bayesian network factorization of bayesian belief functions, they disclaim any need for representation of independence of variables in belief functions.

no code implementations • 12 Jul 2017 • Mieczysław A. Kłopotek

One of the most important open questions seems to be the relationship between frequencies and the Mathematical Theory of Evidence.

no code implementations • 30 Jun 2017 • Mieczysław A. Kłopotek

This paper proposes a new algorithm for recovery of belief network structure from data handling hidden variables.

no code implementations • 8 Jun 2017 • Mieczysław A. Kłopotek, Andrzej Matuszewski

Weaknesses of various proposals of probabilistic interpretation of MTE belief functions are demonstrated.

no code implementations • 8 Jun 2017 • Andrzej Matuszewski, Mieczysław A. Kłopotek

The conditioning in the Dempster-Shafer Theory of Evidence has been defined (by Shafer \cite{Shafer:90} as combination of a belief function and of an "event" via Dempster rule.

no code implementations • 11 May 2017 • Mieczysław A. Kłopotek

It is demonstrated that no increase in the number of points may lead to recovery of structure and motion parameters from two frames only.

no code implementations • 24 Apr 2017 • Mieczysław A. Kłopotek

We define the notion of a well-clusterable data set combining the point of view of the objective of $k$-means clustering algorithm (minimising the centric spread of data elements) and common sense (clusters shall be separated by gaps).

no code implementations • 18 Apr 2017 • Mieczysław A. Kłopotek

In this paper we would like to deny the results of Wang et al. raising two fundamental claims: * A line does not contribute anything to recognition of motion parameters from two images * Four traceable points are not sufficient to recover motion parameters from two perspective To be constructive, however, we show that four traceable points are sufficient to recover motion parameters from two frames under orthogonal projection and that five points are sufficient to simplify the solution of the two-frame problem under orthogonal projection to solving a linear equation system.

no code implementations • 12 Apr 2017 • Mieczysław A. Kłopotek

This paper is devoted to expressiveness of hypergraphs for which uncertainty propagation by local computations via Shenoy/Shafer method applies.

no code implementations • 11 Apr 2017 • Mieczysław A. Kłopotek

It discusses also possibility of simplification of reconstruction of flat curves moving free for prospective projections.

no code implementations • 11 Apr 2017 • Mieczysław A. Kłopotek

Fundamental discrepancy between first order logic and statistical inference (global versus local properties of universe) is shown to be the obstacle for integration of logic and probability in L. p. logic of Bacchus.

no code implementations • 8 Apr 2017 • Mieczysław A. Kłopotek, Sławomir T. Wierzchoń

The interpretation has the property that Given a definition of the belief measure of objects in the interpretation domain we can perform operations in this domain and the measure of the resulting object is derivable from measures of component objects via belief operator.

no code implementations • 4 Mar 2017 • Mieczysław A. Kłopotek

We define also conditions for which clusterability property of the original space is transmitted to the projected space, so that special case algorithms for the original space are also applicable in the projected space.

no code implementations • 20 Feb 2017 • Mieczysław A. Kłopotek

We prove in this paper that the expected value of the objective function of the $k$-means++ algorithm for samples converges to population expected value.

no code implementations • 19 Jan 2017 • Mieczysław A. Kłopotek

This paper corrects the proof of the Theorem 2 from the Gower's paper \cite[page 5]{Gower:1982} as well as corrects the Theorem 7 from Gower's paper \cite{Gower:1986}.

no code implementations • 16 Jan 2017 • Piotr Borkowski, Krzysztof Ciesielski, Mieczysław A. Kłopotek

In this paper we propose a new document classification method, bridging discrepancies (so-called semantic gap) between the training set and the application sets of textual data.

no code implementations • 10 May 2016 • Paweł Łoziński, Dariusz Czerski, Mieczysław A. Kłopotek

Pattern-based methods of IS-A relation extraction rely heavily on so called Hearst patterns.

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