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Wojciech Kwedlo
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2020 – today
- 2024
- [c15]Wojciech Kwedlo:
Parallel Iterative Mistake Minimization (IMM) clustering algorithm for shared-memory systems. ICPP 2024: 1-10 - 2023
- [c14]Wojciech Kwedlo
:
Expectation-Maximization Algorithms for Gaussian Mixture Models Using Linear Algebra Libraries on Parallel Shared-Memory Systems. FedCSIS 2023: 1047-1052 - 2022
- [j6]Wojciech Kwedlo
:
A hybrid steady-state evolutionary algorithm using random swaps for Gaussian model-based clustering. Expert Syst. Appl. 208: 118159 (2022) - 2021
- [j5]Wojciech Kwedlo
, Michal Lubowicz
:
Accelerated K-Means Algorithms for Low-Dimensional Data on Parallel Shared-Memory Systems. IEEE Access 9: 74286-74301 (2021)
2010 – 2019
- 2019
- [j4]Wojciech Kwedlo
, Pawel J. Czochanski:
A Hybrid MPI/OpenMP Parallelization of $K$ -Means Algorithms Accelerated Using the Triangle Inequality. IEEE Access 7: 42280-42297 (2019) - [c13]Wojciech Kwedlo
, Michal Lubowicz:
An OpenMP Parallelization of the K-means Algorithm Accelerated Using KD-trees. PPAM (1) 2019: 457-466 - 2017
- [c12]Wojciech Kwedlo
:
Two Modifications of Yinyang K-means Algorithm. ICAISC (2) 2017: 94-103 - 2015
- [j3]Wojciech Kwedlo
:
A new random approach for initialization of the multiple restart EM algorithm for Gaussian model-based clustering. Pattern Anal. Appl. 18(4): 757-770 (2015) - [c11]Wojciech Kwedlo
:
Using a Genetic Algorithm for Selection of Starting Conditions for the EM Algorithm for Gaussian Mixture Models. CORES 2015: 125-134 - 2014
- [c10]Wojciech Kwedlo
:
A Parallel EM Algorithm for Gaussian Mixture Models Implemented on a NUMA System Using OpenMP. PDP 2014: 292-298 - 2013
- [c9]Wojciech Kwedlo
:
A New Method for Random Initialization of the EM Algorithm for Multivariate Gaussian Mixture Learning. CORES 2013: 81-90 - 2011
- [j2]Wojciech Kwedlo
:
A clustering method combining differential evolution with the K-means algorithm. Pattern Recognit. Lett. 32(12): 1613-1621 (2011) - 2010
- [j1]Krzysztof Bandurski, Wojciech Kwedlo
:
A Lamarckian Hybrid of Differential Evolution and Conjugate Gradients for Neural Network Training. Neural Process. Lett. 32(1): 31-44 (2010) - [c8]Wojciech Kwedlo
, Piotr Iwanowicz:
Using Genetic Algorithm for Selection of Initial Cluster Centers for the K-Means Method. ICAISC (2) 2010: 165-172
2000 – 2009
- 2006
- [c7]Wojciech Kwedlo
, Krzysztof Bandurski:
A Parallel Differential Evolution Algorithm A Parallel Differential Evolution Algorithm. PARELEC 2006: 319-324 - 2005
- [c6]Wojciech Kwedlo
:
Parallelizing Evolutionary Algorithms for Clustering Data. PPAM 2005: 430-438 - 2003
- [c5]Wojciech Kwedlo:
A Parallel Evolutionary Algorithm for Discovery of Decision Rules. PPAM 2003: 580-585 - 2001
- [c4]Wojciech Kwedlo, Marek Kretowski
:
An Evolutionary Algorithm for Cost-Sensitive Decision Rule Learning. ECML 2001: 288-299 - 2000
- [c3]Jörg Keller, Valerij Bauer, Wojciech Kwedlo:
Application of Data-Mining and Knowledge Discovery in Automotive Data Engineering. PKDD 2000: 464-469
1990 – 1999
- 1999
- [c2]Wojciech Kwedlo, Marek Kretowski
:
An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction. PKDD 1999: 392-397 - 1998
- [c1]Wojciech Kwedlo, Marek Kretowski
:
Discovery of Decision Rules from Databases: An Evolutionary Approach. PKDD 1998: 370-378
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