Our prizes, grants and other accomplishments.
See what we can offer you, as a Bachelor, Master of PhD level student.
Interested in our research? Please come in.
Come to our weekly meeting.
Take a quick tour through our team members.
We focus on various machine learning models and algorithms, with particular interest in hybrid models, connecting concepts from both classification and clustering methods.
GMUM.r is an R package done in a close collaboration between team members and students. This is an unique occasion to make a first step into true science. We encourage all students to visit a section for students as well as contact Wojciech Czarnecki (project coordinator) in order to get more details.
Hierarchical Classifier with Overlaping Clusters is a novel ensemble model designed to work with problems with numerous output labels. It is being developed mainly by dr hab. Igor Podolak, polish speaking people may be interested in the new book describing this classifier in detail.
Cross Entropy Clustering is a novel clustering method developed by dr hab. Jacek Tabor and his PhD students. It finds a compromise between easy and efficient implementation (similar to the k-means) and strengths of the model based clustering (Expectation Maximization). We are currently working on the generalizations of this concept and applications in the classification.