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- Marek Grochowski, Norbert Jankowski
- ICAISC
- 2004

This paper is an continuation of the accompanying paper with the same main title. The first paper reviewed instance selection algorithms, here results of empirical comparison and comments areâ€¦ (More)

- Norbert Jankowski, Marek Grochowski
- ICAISC
- 2004

Several methods were proposed to reduce the number of instances (vectors) in the learning set. Some of them extract only bad vectors while others try to remove as many instances as possible withoutâ€¦ (More)

- Marek Grochowski, Robert Schaefer, Piotr Uhruski
- PPAM
- 2003

- Marek Grochowski, Wlodzislaw Duch
- Constructive Neural Networks
- 2009

Learning from data with complex non-local relations and multimodal class distribution for widely used classification algorithms is still very hard. Even if accurate solution is found the resultingâ€¦ (More)

- Norbert Jankowski, Marek Grochowski
- Artificial Intelligence and Applications
- 2005

This paper can be seen from two sides. From the first side as the answer of the question: how to initialize the Learning Vectors Quantization algorithm. And from second side it can be seen as theâ€¦ (More)

- Wlodzislaw Duch, Tomasz Maszczyk, Marek Grochowski
- Meta-Learning in Computational Intelligence
- 2011

Meta-learning has many aspects, but its final goal is to discover in an automatic way many interesting models for a given data. Our early attempts in this area involved heterogeneous learning systemsâ€¦ (More)

- Marek Grochowski
- ICAISC
- 2012

Instance selection methods are very useful data mining tools for dealing with large data sets. There exist many instance selection algorithms capable for significant reduction of training data sizeâ€¦ (More)

- Marek Grochowski, Wlodzislaw Duch
- ICAISC
- 2008

Learning in cases that are almost linearly separable is easy, but for highly non-separable problems all standard machine learning methods fail. Many strategies to build adaptive systems are based onâ€¦ (More)

- Marek Grochowski, Robert Schaefer, Wojciech Toporkiewicz, Piotr Uhruski
- PARELEC
- 2002

Smart Solid is a complex, agent-based approach to a CAE system. Every agent contains a complete set of facilities necessary for a CAE process, as well as a new, local load balancing mechanism, theâ€¦ (More)

- Marek Grochowski, Ewa Tusha, Piotr Uhruski
- Inteligencia Artificial, Revista Iberoamericanaâ€¦
- 2005

The paper briefly presents the architecture of a multi-agent computing system with an emphasis on diffusion scheduling. Two binding energy formulas used by the diffusion scheduling algorithm areâ€¦ (More)