Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Jacek Koronacki"'
Publikováno v:
Information Sciences. 330:74-87
Dimensionality reduction that preserves certain characteristics of data is needed for numerous reasons. In this work we focus on data coming from a mixture of Gaussian distributions and we propose a method that preserves the distinctness of the clust
Publikováno v:
Applied Mathematics and Computation. 256:591-601
There are numerous measures designed to evaluate quality of a given data grouping in terms of its distinctness and between-cluster separation. However, there seems to be no efficient method to assess distinctness of the intrinsic structure within dat
Autor:
Jacek Koronacki
Publikováno v:
Mathematica Applicanda. 11
Autor:
Jacek Koronacki, W. Wertz
Publikováno v:
Mathematica Applicanda. 13
In the paper a survey of the asymptotic theory of recursive estimation of probability densities is given. Stress is laid on pointwise properties. In particular, asymptotic unbiasedness and consistency under possibly minimal assumptions and the rates
Autor:
Jan Komorowski, Jakub Mieczkowski, Marcin Kruczyk, Nicholas Baltzer, Michał Dramiński, Jacek Koronacki
Publikováno v:
Fundamenta Informaticae. 127:273-288
An important step prior to constructing a classifier for a very large data set is feature selection. With many problems it is possible to find a subset of attributes that have the same discriminative power as the full data set. There are many feature
Autor:
Jacek Koronacki
Publikováno v:
Mathematica Applicanda. 42
Coraz wiecej sygnalow wskazuje, ze zmienia sie stosunek spoleczności matematykow do wyzej wymienionej kwestii. Do niedawna stopnie naukowe i tytul naukowy z nauk matematycznych mialy byc przyznawane jedynie za tworczy wklad w rozwoj tej dziedziny. O
Publikováno v:
Pattern Recognition. 38:241-250
We propose a new algorithm for positron emission tomography (PET) image reconstruction. The algorithm belongs to the family of Markov chain Monte Carlo methods with auxiliary variables. The idea is to iteratively generate hidden variables at one step
Autor:
Jacek Koronacki, Jan Ćwik
Publikováno v:
Computational Statistics & Data Analysis. 26:199-218
A multivariate extension of the plug-in kernel (and filtered kernel) estimator is proposed and this uses asymptotically optimal bandwidth matrix (matrices) for a normal mixture approximation of a density to be estimated (the filtered kernel estimator
Autor:
Jacek Koronacki, Jan Ćwik
Publikováno v:
Neural Computing & Applications. 6:173-185
This paper is a continuation of the authors' earlier work [1], where a version of the Traven's [2] Gaussian clustering neural network (being a recursive counterpart of the EM algorithm) has been investigated. A comparative simulation study of the Gau
Autor:
Jacek Koronacki, Jan Ćwik
Publikováno v:
Neural Computing & Applications. 4:149-160
A version of the Traven's [1] Gaussian clustering algorithm for normal mixture densities is studied. Unlike in the case of the Traven's algorithm, no constraints on covariance structure of mixture components are imposed. Simulations suggest that the