activity
20102023
most citedAn Aposteriorical Clusterability Criterion for -Means++ and Simplicity of Clustering

7 citations · 28 across the 48 of their papers we have counts for

collaborators

53 papers

cs.LG2023

Eigenvalue-based Incremental Spectral Clustering

Mieczysław A. Kłopotek, Bartłmiej Starosta, Sławomir T. Wierzchoń

Our previous experiments demonstrated that subsets collections of (short) documents (with several hundred entries) share a common normalized in some way eigenvalue spectrum of comb…

cs.LG2023

Wide Gaps and Clustering Axioms

Mieczysław A. Kłopotek

The widely applied k-means algorithm produces clusterings that violate our expectations with respect to high/low similarity/density and is in conflict with Kleinberg's axiomatic sy…

cs.LG2023

Are Easy Data Easy (for K-Means)

Mieczysław A. Kłopotek

This paper investigates the capability of correctly recovering well-separated clusters by various brands of the -means algorithm. The concept of well-separatedness used here is…

cs.LG2023★ 1 cited

Explainable Graph Spectral Clustering of Text Documents

Bartłomiej Starosta, Mieczysław A. Kłopotek, Sławomir T. Wierzchoń

Spectral clustering methods are known for their ability to represent clusters of diverse shapes, densities etc. However, results of such algorithms, when applied e.g. to text docum…

cs.LG2022

High-Dimensional Wide Gap -Means Versus Clustering Axioms

Mieczysław A. Kłopotek

Kleinberg's axioms for distance based clustering proved to be contradictory. Various efforts have been made to overcome this problem. Here we make an attempt to handle the issue by…

cs.AI2022

How To Overcome Richness Axiom Fallacy

Mieczysław A. Kłopotek, Robert A. Kłopotek

The paper points at the grieving problems implied by the richness axiom in the Kleinberg's axiomatic system and suggests resolutions. The richness induces learnability problem in g…

cs.AI2022★ 3 cited

Towards Continuous Consistency Axiom

Mieczyslaw A. Klopotek, Robert A. Klopotek

Development of new algorithms in the area of machine learning, especially clustering, comparative studies of such algorithms as well as testing according to software engineering pr…

cs.LG2022

A Clustering Preserving Transformation for k-Means Algorithm Output

Mieczysław A. Kłopotek

This note introduces a novel clustering preserving transformation of cluster sets obtained from -means algorithm. This transformation may be used to generate new labeled data{}s…

cs.AI2020

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

Mieczysław A. Kłopotek

Spirtes, Glymour and Scheines formulated a Conjecture that a direct dependence test and a head-to-head meeting test would suffice to construe directed acyclic graph decompositions…

cs.AI2020

On Irrelevance of Attributes in Flexible Prediction

Mieczyslaw A. Klopotek, Andrzej Matuszewski

This paper analyses properties of conceptual hierarchy obtained via incremental concept formation method called "flexible prediction" in order to determine what kind of "relevance"…

cs.AI2020★ 1 cited

Non-Destructive Sample Generation From Conditional Belief Functions

Mieczysław A. Kłopotek

This paper presents a new approach to generate samples from conditional belief functions for a restricted but non trivial subset of conditional belief functions. It assumes the fac…

cs.LG2019

A Note On k-Means Probabilistic Poverty

Mieczysław A. Kłopotek

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

cs.AI2019

Query Optimization Properties of Modified VBS

Mieczysław A. Kłopotek, Sławomir T. Wierzchoń

Valuation-Based~System can represent knowledge in different domains including probability theory, Dempster-Shafer theory and possibility theory. More recent studies show that the f…

cs.AI2018

Reasoning and Facts Explanation in Valuation Based Systems

S. T. Wierzchoń, M. A. Kłopotek, M. Michalewicz

In the literature, the optimization problem to identify a set of composite hypotheses H, which will yield the largest where a composite hypothesis is an instantiatio…

cs.AI2018

Factorization of Dempster-Shafer Belief Functions Based on Data

Andrzej Matuszewski, Mieczysław A. Kłopotek

One important obstacle in applying Dempster-Shafer Theory (DST) is its relationship to frequencies. In particular, there exist serious difficulties in finding factorizations of bel…

cs.CV2018

Rigid Body Structure and Motion From Two-Frame Point-Correspondences Under Perspective Projection

Mieczysław A. Kłopotek

This paper is concerned with possibility of recovery of motion and structure parameters from multiframes under perspective projection when only points on a rigid body are traced. F…

cs.AI2018

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

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. The seriousness of th…

cs.CV2018

Structure and Motion from Multiframes

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.

cs.AI2018

Reasoning From Data in the Mathematical Theory of Evidence

Mieczysław Kłopotek

Mathematical Theory of Evidence (MTE) is known as a foundation for reasoning when knowledge is expressed at various levels of detail. Though much research effort has been committed…

cs.AI2018

Mathematical Theory of Evidence Versus Evidence

Mieczysław Kłopotek

This paper is concerned with the apparent greatest weakness of the Mathematical Theory of Evidence (MTE) of Shafer \cite{Shafer:76}, which has been strongly criticized by Wasserman…

cs.AI2018★ 1 cited

Dempsterian-Shaferian Belief Network From Data

Mieczysław A. Kłopotek

Shenoy and Shafer {Shenoy:90} demonstrated that both for Dempster-Shafer Theory and probability theory there exists a possibility to calculate efficiently marginals of joint belief…

cs.AI2018★ 1 cited

Too Fast Causal Inference under Causal Insufficiency

Mieczysław A. Kłopotek

Causally insufficient structures (models with latent or hidden variables, or with confounding etc.) of joint probability distributions have been subject of intense study not only i…

cs.AI2017

Fast Restricted Causal Inference

Mieczysław A. Kłopotek

Hidden variables are well known sources of disturbance when recovering belief networks from data based only on measurable variables. Hence models assuming existence of hidden varia…

cs.AI2017

On (Anti)Conditional Independence in Dempster-Shafer Theory

Mieczysław A. Kłopotek

This paper verifies a result of {Shenoy:94} concerning graphoidal structure of Shenoy's notion of independence for Dempster-Shafer theory of belief functions. Shenoy proved that hi…