Statistical Control of RBF-like Networks for Classification. - Norbert Jankowski; Visakan Kadirkamanathan (ICANN, 1997)

Optimization and Interpretation of Rule-based Classifiers. - Wlodzislaw Duch; Norbert Jankowski; Krzysztof Grabczewski; Rafal Adamczak (Intelligent Information Systems, 2000)

Taxonomy of Neural Transfer Functions. - Wlodzislaw Duch; Norbert Jankowski (IJCNN (3), 2000)

Transfer functions: hidden possibilities for better neural networks. - Wlodzislaw Duch; Norbert Jankowski (ESANN, 2001)

Optimal transfer function neural networks. - Norbert Jankowski; Wlodzislaw Duch (ESANN, 2001)

Transformations of Symbolic Data for Continuous Data Oriented Models. - Krzysztof Grabczewski; Norbert Jankowski (ICANN, 2003)

Discrete feature weighting & selection algorithm. - Norbert Jankowski (IJCNN, 2003)

Comparison of Instance Selection Algorithms II. Results and Comments. - Marek Grochowski; Norbert Jankowski (ICAISC, 2004)

Comparison of Instances Seletion Algorithms I. Algorithms Survey. - Norbert Jankowski; Marek Grochowski (ICAISC, 2004)

Instances Selection Algorithms in the Conjunction with LVQ. - Norbert Jankowski; Marek Grochowski (Artificial Intelligence and Applications, 2005)

Feature Selection with Decision Tree Criterion. - Krzysztof Grabczewski; Norbert Jankowski (HIS, 2005)

Heterogenous Committees with Competence Analysis. - Norbert Jankowski; Krzysztof Grabczewski (HIS, 2005)

Mining for Complex Models Comprising Feature Selection and Classification. - Krzysztof Grabczewski; Norbert Jankowski (Feature Extraction, 2006)

Learning Machines. - Norbert Jankowski; Krzysztof Grabczewski (Feature Extraction, 2006)

Versatile and Efficient Meta-Learning Architecture: Knowledge Representation and Management in Computational Intelligence. - Krzysztof Grabczewski; Norbert Jankowski (CIDM, 2007)

Handwritten Digit, Recognition Road to Contest victory. - Norbert Jankowski; Krzysztof Grabczewski (CIDM, 2007)

Meta-learning with Machine Generators and Complexity Controlled Exploration. - Krzysztof Grabczewski; Norbert Jankowski (ICAISC, 2008)

Building meta-learning algorithms basing on search controlled by machine complexity. - Norbert Jankowski; Krzysztof Grabczewski (IJCNN, 2008)

Learning Machines Information Distribution System with Example Applications. - Norbert Jankowski; Krzysztof Grabczewski (Computer Recognition Systems 2, 2008)

Task Management in Advanced Computational Intelligence System. - Krzysztof Grabczewski; Norbert Jankowski (ICAISC (1), 2010)

Increasing Efficiency of Data Mining Systems by Machine Unification and Double Machine Cache. - Norbert Jankowski; Krzysztof Grabczewski (ICAISC (1), 2010)

Complexity Measures for Meta-learning and Their Optimality. - Norbert Jankowski (Algorithmic Probability and Friends, 2011)

Analysis of Feature Weighting Methods Based on Feature Ranking Methods for Classification. - Norbert Jankowski; Krzysztof Usowicz (ICONIP (2), 2011)

Saving time and memory in computational intelligence system with machine unification and task spooling. - Krzysztof Grabczewski; Norbert Jankowski (Knowl. Based Syst., 2011)

Universal Meta-Learning Architecture and Algorithms. - Norbert Jankowski; Krzysztof Grabczewski (Meta-Learning in Computational Intelligence, 2011)

Make it cheap: Learning with O(nd) complexity. - Wlodzislaw Duch; Norbert Jankowski; Tomasz Maszczyk (IJCNN, 2012)

Graph-based generation of a meta-learning search space. - Norbert Jankowski (Int. J. Appl. Math. Comput. Sci., 2012)

Fast heterogeneous boosting. - Norbert Jankowski (CIEL, 2013)

The Multi-Ranked Classifiers Comparison. - Norbert Jankowski (CORES, 2015)

Prototype-Based Kernels for Extreme Learning Machines and Radial Basis Function Networks. - Norbert Jankowski (ICAISC (1), 2018)

Comparison of Prototype Selection Algorithms Used in Construction of Neural Networks Learned by SVD. - Norbert Jankowski (Int. J. Appl. Math. Comput. Sci., 2018)

Fast Algorithm for Prototypes Selection - Trust-Margin Prototypes. - Norbert Jankowski; Marek Orlinski (ICAISC (1), 2019)

Fast Encoding length-based prototype selection algorithms. - Norbert Jankowski; Marek Orlinski (Aust. J. Intell. Inf. Process. Syst., 2019)

A Fast Neural Network Learning Algorithm with Approximate Singular Value Decomposition. - Norbert Jankowski; Rafal Linowiecki (Int. J. Appl. Math. Comput. Sci., 2019)

O (m log m) instance selection algorithms - RR-DROPs. - Marek Orlinski; Norbert Jankowski (IJCNN, 2020)

Fast t-SNE algorithm with forest of balanced LSH trees and hybrid computation of repulsive forces. - Marek Orlinski; Norbert Jankowski (Knowl. Based Syst., 2020)

Revdbscan and Flexscan - O(nlog n) Clustering Algorithms. - Norbert Jankowski (ICONIP (5), 2021)

A Fast and Efficient Algorithm for Filtering the Training Dataset. - Norbert Jankowski (ICONIP (1), 2022)

Automatic Kernel Construction During the Neural Network Learning by Modified Fast Singular Value Decomposition. - Norbert Jankowski; Grzegorz Dudek (ICCS (3), 2024)

Instance Selection by Fast Local Set Border Selector. - Norbert Jankowski; Mateusz Skarupski (ICCS (4), 2025)