Search Results for author: Mieczysław A. Kłopotek

Found 28 papers, 0 papers with code

p-d-Separation -- A Concept for Expressing Dependence/Independence Relations in Causal Networks

no code implementations15 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.

A Note On $k$-Means Probabilistic Poverty

no code implementations28 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}.

Query Optimization Properties of Modified VBS

no code implementations26 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.

Factorization of Dempster-Shafer Belief Functions Based on Data

no code implementations14 Dec 2018 Andrzej Matuszewski, Mieczysław A. Kłopotek

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

On Marginally Correct Approximations of Dempster-Shafer Belief Functions from Data

no code implementations7 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.

Structure and Motion from Multiframes

no code implementations30 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.

Dempsterian-Shaferian Belief Network From Data

no code implementations6 Jun 2018 Mieczysław A. Kłopotek

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

Too Fast Causal Inference under Causal Insufficiency

no code implementations30 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.

Causal Inference

Fast Restricted Causal Inference

no code implementations13 Jul 2017 Mieczysław A. Kłopotek

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

Causal Inference

On (Anti)Conditional Independence in Dempster-Shafer Theory

no code implementations13 Jul 2017 Mieczysław A. Kłopotek

It excludes especially so-called probabilistic belief functions.

Independence, Conditionality and Structure of Dempster-Shafer Belief Functions

no code implementations12 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.

Identification and Interpretation of Belief Structure in Dempster-Shafer Theory

no code implementations12 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.

Restricted Causal Inference Algorithm

no code implementations30 Jun 2017 Mieczysław A. Kłopotek

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

Causal Inference

Evidence Against Evidence Theory (?!)

no code implementations8 Jun 2017 Mieczysław A. Kłopotek, Andrzej Matuszewski

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

What Does a Belief Function Believe In ?

no code implementations8 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.

Distribution of degrees of freedom over structure and motion of rigid bodies

no code implementations11 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.

An Aposteriorical Clusterability Criterion for $k$-Means++ and Simplicity of Clustering

no code implementations24 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).

Common Sense Reasoning

A Comment on "Analysis of Video Image Sequences Using Point and Line Correspondences"

no code implementations18 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.

Beliefs in Markov Trees - From Local Computations to Local Valuation

no code implementations12 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.

Reconstruction of~3-D Rigid Smooth Curves Moving Free when Two Traceable Points Only are Available

no code implementations11 Apr 2017 Mieczysław A. Kłopotek

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

Beliefs and Probability in Bacchus' l.p. Logic: A~3-Valued Logic Solution to Apparent Counter-intuition

no code implementations11 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.

Basic Formal Properties of A Relational Model of The Mathematical Theory of Evidence

no code implementations8 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.

Machine Learning Friendly Set Version of Johnson-Lindenstrauss Lemma

no code implementations4 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.

On the Consistency of $k$-means++ algorithm

no code implementations20 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.

Validity of Clusters Produced By kernel-$k$-means With Kernel-Trick

no code implementations19 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}.

Semantic classifier approach to document classification

no code implementations16 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.

Classification Document Classification +1

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