Norbert Jankowski - researchr alias

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Viewing Publication 1 - 38 from 38

2024

Automatic Kernel Construction During the Neural Network Learning by Modified Fast Singular Value DecompositionNorbert Jankowski, Grzegorz Dudek. iccs 2024: 205-212 [doi]

2022

A Fast and Efficient Algorithm for Filtering the Training DatasetNorbert Jankowski. iconip 2023: 504-512 [doi]

2021

Revdbscan and Flexscan - O(nlog n) Clustering AlgorithmsNorbert Jankowski. iconip 2021: 642-650 [doi]

2020

O (m log m) instance selection algorithms - RR-DROPsMarek Orlinski, Norbert Jankowski. ijcnn 2020: 1-8 [doi]

Fast t-SNE algorithm with forest of balanced LSH trees and hybrid computation of repulsive forcesMarek Orlinski, Norbert Jankowski. kbs, 206:106318, 2020. [doi]

2019

Fast Algorithm for Prototypes Selection - Trust-Margin PrototypesNorbert Jankowski, Marek Orlinski. icaisc 2019: 583-594 [doi]

Fast Encoding length-based prototype selection algorithmsNorbert Jankowski, Marek Orlinski. ajiips, 16(3):61-66, 2019. [doi]

A Fast Neural Network Learning Algorithm with Approximate Singular Value DecompositionNorbert Jankowski, Rafal Linowiecki. amcs, 29(3):581-594, 2019. [doi]

2018

Prototype-Based Kernels for Extreme Learning Machines and Radial Basis Function NetworksNorbert Jankowski. icaisc 2018: 70-75 [doi]

Comparison of Prototype Selection Algorithms Used in Construction of Neural Networks Learned by SVDNorbert Jankowski. amcs, 28(4):719-733, 2018. [doi]

2015

The Multi-Ranked Classifiers ComparisonNorbert Jankowski. cores 2016: 111-123 [doi]

2013

Fast heterogeneous boostingNorbert Jankowski. ciel 2013: 1-8 [doi]

2012

Make it cheap: Learning with O(nd) complexityWlodzislaw Duch, Norbert Jankowski, Tomasz Maszczyk. ijcnn 2012: 1-4 [doi]

Graph-based generation of a meta-learning search spaceNorbert Jankowski. amcs, 22(3):647-667, 2012. [doi]

2011

Saving time and memory in computational intelligence system with machine unification and task spoolingKrzysztof Grabczewski, Norbert Jankowski. kbs, 24(5):570-588, 2011. [doi]

Complexity Measures for Meta-learning and Their OptimalityNorbert Jankowski. BIRTHDAY 2013: 198-210 [doi]

Analysis of Feature Weighting Methods Based on Feature Ranking Methods for ClassificationNorbert Jankowski, Krzysztof Usowicz. iconip 2011: 238-247 [doi]

Universal Meta-Learning Architecture and AlgorithmsNorbert Jankowski, Krzysztof Grabczewski. In Norbert Jankowski, Wlodzislaw Duch, Krzysztof Grabczewski, editors, Meta-Learning in Computational Intelligence. Volume 358 of Studies in Computational Intelligence, pages 1-76, Springer, 2011. [doi]

2010

Task Management in Advanced Computational Intelligence SystemKrzysztof Grabczewski, Norbert Jankowski. icaisc 2010: 331-338 [doi]

Increasing Efficiency of Data Mining Systems by Machine Unification and Double Machine CacheNorbert Jankowski, Krzysztof Grabczewski. icaisc 2010: 380-387 [doi]

2008

Meta-learning with Machine Generators and Complexity Controlled ExplorationKrzysztof Grabczewski, Norbert Jankowski. icaisc 2008: 545-555 [doi]

Building meta-learning algorithms basing on search controlled by machine complexityNorbert Jankowski, Krzysztof Grabczewski. ijcnn 2008: 3601-3608 [doi]

Learning Machines Information Distribution System with Example ApplicationsNorbert Jankowski, Krzysztof Grabczewski. In Marek Kurzynski, Edward Puchala, Michal Wozniak, Andrzej Zolnierek, editors, Computer Recognition Systems 2. Volume 45 of Advances in Soft Computing, pages 205-215, Springer, 2008. [doi]

2007

Versatile and Efficient Meta-Learning Architecture: Knowledge Representation and Management in Computational IntelligenceKrzysztof Grabczewski, Norbert Jankowski. cidm 2007: 51-58 [doi]

Handwritten Digit, Recognition Road to Contest victoryNorbert Jankowski, Krzysztof Grabczewski. cidm 2007: 491-498 [doi]

2006

Mining for Complex Models Comprising Feature Selection and ClassificationKrzysztof Grabczewski, Norbert Jankowski. In Isabelle Guyon, Masoud Nikravesh, Steve R. Gunn, Lotfi A. Zadeh, editors, Feature Extraction - Foundations and Applications. Volume 207 of Studies in Fuzziness and Soft Computing, pages 471-488, Springer, 2006. [doi]

Learning MachinesNorbert Jankowski, Krzysztof Grabczewski. In Isabelle Guyon, Masoud Nikravesh, Steve R. Gunn, Lotfi A. Zadeh, editors, Feature Extraction - Foundations and Applications. Volume 207 of Studies in Fuzziness and Soft Computing, pages 29-64, Springer, 2006. [doi]

2005

Feature Selection with Decision Tree CriterionKrzysztof Grabczewski, Norbert Jankowski. his 2005: 212-217 [doi]

Instances Selection Algorithms in the Conjunction with LVQNorbert Jankowski, Marek Grochowski. aia 2005: 703-708

Heterogenous Committees with Competence AnalysisNorbert Jankowski, Krzysztof Grabczewski. his 2005: 417-424 [doi]

2004

Comparison of Instance Selection Algorithms II. Results and CommentsMarek Grochowski, Norbert Jankowski. icaisc 2004: 580-585 [doi]

Comparison of Instances Seletion Algorithms I. Algorithms SurveyNorbert Jankowski, Marek Grochowski. icaisc 2004: 598-603 [doi]

2003

Transformations of Symbolic Data for Continuous Data Oriented ModelsKrzysztof Grabczewski, Norbert Jankowski. icann 2003: 359-366 [doi]

2001

Transfer functions: hidden possibilities for better neural networksWlodzislaw Duch, Norbert Jankowski. esann 2001: 81-94 [doi]

Optimal transfer function neural networksNorbert Jankowski, Wlodzislaw Duch. esann 2001: 101-106 [doi]

2000

Taxonomy of Neural Transfer FunctionsWlodzislaw Duch, Norbert Jankowski. ijcnn 2000: 477-484 [doi]

Optimization and Interpretation of Rule-based ClassifiersWlodzislaw Duch, Norbert Jankowski, Krzysztof Grabczewski, Rafal Adamczak. iiswc 2000: 1-13

1997

Statistical Control of RBF-like Networks for ClassificationNorbert Jankowski, Visakan Kadirkamanathan. icann 1997: 385-390

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