Tomáš Řehořek

Homepage at FIT CTU in Prague

Personal info

Ing. Tomáš Řehořek
E-mail: tomas[dot]rehorek(at)fit[dot]cvut[dot]cz
LinkedIn profile
Professional interests:
- Data Mining, Recommender systems
- Evolutionary Computation, Artificial Neural Networks
- Python, JavaScript, Java, Parallel Systems
Member of Computational Intelligence Group (CIG) at FIT CTU in Prague
Supervisor: Ing. Pavel Kordík, Ph.D.

Rehorek, T., Kordik, P.: A Soft Computing Approach to Knowledge Flow Synthesis and Optimization. In Soft Computing Models in Industrial and Environmental Applications, Vol. 188, Springer Berlin Heidelberg, ISBN 978-3-642-32922-7.
Rehorek, T., Kordik, P.: Using Interactive Evolution for Exploratory Data Analysis (PDF). In Proceedings of the 6th International Scientific and Technical Conference (CSIT'2011), Lviv, UA, LPNU, 2011, pp. 131--135, ISBN 978-966-2191-04-2.
Kuznetsov, S., Kordik, P., Rehorek, T., Dvorak, J., Kroha, P.: Reducing cold start problems in educational recommender systems. 2016 International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, pp. 3143-3149.
Rehorek, T., Biza, O., Bartyzal, R., Kordik, P., Povalyaev, I., Podsztavek, O.: Comparing offline and online evaluation results of recommender systems (PDF). REVEAL 2018, a RecSys 2018 workshop.

2014: KEG: Recommender Systems (PDF)
2013: Doctoral Study Report: Multiobjective Optimization in Recommender Systems using Ensemble Methods (PDF),
2012: Soco'2012: A Soft-Computing Approach to Knowledge Flow Synthesis and Optimization (PDF),
2011: CIG: Interactive Evolution in Automated Knowledge Discovery (PPT),
2011: CSIT'11: Using Interactive Evolution for Exploratory Data Analysis (PPT)
2011: [Czech] PI-NSV: Pokročilé metody učení neuronových sítí (PDF, PPT)

Radek Bartyzal: Deep Latent Factor Models for Recommender Systems (Master's Thesis, in progress)

Petr Kasalický: Content-Based Recommendation Model Trained Using Interaction Similarity (Bachelor's Thesis, received Dean's award)
Ladislav Martínek: Evaluation of Local Sensitive Hashing (LSH) Algorithm in Recommender Systems (Bachelor's Thesis, received Dean's award)
Martin Pavlíček: Recommendation Models Based on Images (Bachelor's Thesis)

Michal Bajer: Framework for evaluation of frequent sequences algorithms in Recommender Systems (Bachelor's Thesis, received Dean's award)

Filip Křesťan: Evaluation of Distributed Database Systems in Context of Personalized Recommendation (Bachelor's Thesis, received Dean's award)
Michal Režnický: Design and Implementation of Feature Selection Module in Recommender System (Bachelor's Thesis)
Tomáš Richtr: Evaluation of Matrix Factorization Algorithms in Collaborative Filtering (Master's Thesis)

Martin Barus: Content Recommendation using Text Mining Methods (Bachelor's Thesis)
Tomáš Fedor: Recommender System for Online Gaming Discount Portal (Bachelor's Thesis, received Dean's award)
Tomáš Frýda: Comparison of Different Neuroevolution Algorithms on Several Problem Domains (Bachelor's Thesis)
Martin Hak: Comparison of Various Success Measures in Collaborative Filtering (Bachelor's Thesis)
Tomáš Richtr: Advanced Gradient Optimization Methods of Artificial Neural Networks in RapidMiner 5 (Bachelor's Thesis, received Dean's award)
David Šenkýř: Interactive Geometric Sketchpad for Web Client (Bachelor's Thesis)

Michal Kvasnička: Vector Graphics Editor for Web Client (Bachelor's Thesis)
Jakub Melezínek: Web Environment for Algorithms on Binary Trees (Bachelor's Thesis, link, received Dean's award)
Jakub Pištěk: Analysis of Collaborative Filtering Algorithms on Multimedial Data (Master's Thesis)
Vít Steklý: Tool for Analysis of Artificial Neural Networks (Bachelor's Thesis)
David Šolc: Web Framework for Stepping and Visualization of Algorithms (Bachelor's Thesis)
Radmir Usmanov: Client-Server Application for Two Player Games using WebSocket (Bachelors's Thesis)