Jirka Vomlel

Institute of Information Theory and Automation (ÚTIA)
Academy of Sciences of the Czech Republic
Pod vodárenskou věží 4,
182 08 Praha 8,
Czech Republic

Phone:	+420-266-052-398
E-mail:
Info:	Google Scholar Profile

Conferences our group have (co-)organized

WUPES'12 - 9th Workshop on Uncertainty Processing, Marianske Lazne, Czech Republic
WUPES'09 - 8th Workshop on Uncertainty Processing, Liblice, Czech Republic
PGM'06 - 3rd European Workshop on Probabilistic Graphical Models, Prague, Czech Republic
WUPES'06 - 7th Workshop on Uncertainty Processing, Mikulov, Czech Republic
WUPES'03 - 6th Workshop on Uncertainty Processing, Hejnice, Czech Republic

Research interests

Uncertainty in Artificial Intelligence,
Probabilistic Methods in Artificial Intelligence,
Bayesian Networks,
Computerized Adaptive Testing (CAT),
Decision Theoretic Troubleshooting, and
Marginal Problem.

Recent research projects

Project GA201/09/1891 - Multidimensional Models of Uncertainty (2009-2011, GA0/GA)

Project GA201/08/0539 - Conditional independence structures: graphical and algebraic approaches (2008-2012, GA0/GA)

Project GEICC/08/E010 - The logic of causal and probabilistic reasoning in uncertain environments (2008-2011, GA0/GE)
The homepage of the project is here.

Project 2C06019 - (Medical) Knowledge Acquisition and Modelling (2006-2011, MSM/2C)
The homepage of the project is here.

Project 1M0572 - Data, algorithms, decision making (2005-2011, MSM/1M)
The homepage of the project is here.

Education

1992 - 2000: Ph.D. in Artificial Intelligence,; Faculty of Electrical Engineering of the Czech Technical University in Prague
1987 - 1992: MSc. in Technical Cybernetics,; Faculty of Electrical Engineering of the Czech Technical University in Prague
1983 - 1987: Gymnazium (High School) in Jihlava, specialization in Electronics

Employment history

2006 - now: Faculty of Management; University of Economics, Jindrichuv Hradec
1994 - 1999, 2002 - now: Department of Decision-making Theory,; Institute of Information Theory and Automation of Academy of Sciences of the Czech Republic
1997 - 2000, 2002 - 2004: Laboratory for Intelligent Systems (LISp),; University of Economics,Prague
1999 - 2002: The Research Unit of Decision Support Systems,; Aalborg University, Denmark.
1992 - 1994: Transcom Ltd. Prague

Book Chapters

[2007]

J. Vomlel and M. Studený, Graphical and Algebraic Representatives of Conditional Independence Models. A chapter in Advances in Probabilistic Graphical Models, Series: Studies in Fuzziness and Soft Computing , Vol. 213, Lucas, Peter; Gámez, José A.; Salmerón, Antonio (Eds.), pp. 55-80, Springer, 2007. ISBN: 978-3-540-68994-2. A preliminary version is available here.

Journal Publications

[2012]	T. Ottosen and J. Vomlel, All roads lead to Rome—New search methods for the optimal triangulation problem, International Journal of Approximate Reasoning, Vol. 53, Issue 9, 2012, pp. 1350–1366. DOI: 10.1016/j.ijar.2012.06.006 . A preliminary version is available here.
[2011]	J. Vomlel, Rank of tensors of l-out-of-k functions: an application in probabilistic inference, Kybernetika, Vol. 47, No. 3, pp. 317-336, 2011. See a version with typos/errors corrected.
[2011]	M. Studený and J. Vomlel, On open questions in the geometric approach to structural learning Bayesian nets. International Journal of Approximate Reasoning, Volume 52, Issue 5, July 2011, Pages 627-640.
[2010]	M. Studený, J. Vomlel, and R. Hemmecke, A geometric view on learning Bayesian network structures, International Journal of Approximate Reasoning. Vol.51, 5 (2010), pp. 573-586, DOI: 10.1016/j.ijar.2010.01.014 A preliminary version is available here.
[2008]	M. Studený and J. Vomlel, A reconstruction algorithm for the essential graph, International Journal of Approximate Reasoning, Volume 50, Issue 2, February 2009, Pages 385-413 . DOI: 10.1016/j.ijar.2008.09.001 . A preliminary version is available here.
[2008]	F. Rijmen and J. Vomlel, Assessing the performance of variational methods for mixed logistic regression models, Journal of Statistical Computation and Simulation, Vol. 78, No. 8, August 2008, 765–779. DOI:10.1080/00949650701282507 . A preliminary version is available here.
[2007]	P. Savický and J. Vomlel, Exploiting tensor rank-one decomposition in probabilistic inference, Kybernetika, Vol. 43, Number 5 (Special Issue dedicated to the memory of Albert Perez), pp. 747-764, 2007. An almost final version is available here.
[2006]	J. Vomlel, Noisy-or classifier. International Journal of Intelligent Systems, Volume 21, Issue 3 (March 2006), pp. 381-398. A preliminary version (but with several typos corrected) is available here. The Reuters dataset (preprocessed by G. Karciauskas) used for experiments is available here. The C++ code that implements the learning and testing of the noisy-or classifier is available on request.
[2004]	J. Vomlel, Probabilistic reasoning with uncertain evidence, Neural Network World, International Journal on Neural and Mass-Parallel Computing and Information Systems, Vol. 14, No. 5/2004, pp. 453-465.
[2004]	J. Vomlel, Integrating inconsistent data in a probabilistic model, Journal of Applied Non-Classical Logics, Vol. 14, No. 3/2004, pp. 365-386. A preliminary version is available here.
[2004]	J. Vomlel, Building Adaptive Tests using Bayesian networks, Kybernetika, Volume 40, Number 3, 2004, pp. 333 - 348. (a preprint version)
[2004]	Y.-G. Kim, M. Valtorta, J. Vomlel, A Prototypical System for Soft Evidential Update, Applied Intelligence, Vol. 21, Issue 1, July - August 2004, pp. 81 - 97.
[2004]	J. Vomlel: Bayesian networks in educational testing, International Journal of Uncertainty, Fuzziness and Knowledge Based Systems, Vol. 12, Supplementary Issue 1, 2004, pp. 83-100. A draft version.
[2003]	M. Vomlelová and J. Vomlel: Troubleshooting: NP-hardness and solution methods, Soft Computing Journal, Volume 7, Number 5, April 2003, pp. 357-368. Online version available from SpringerLink and a draft version (with improved AO* algorithm).
[2002]	M. Valtorta, Y.-G. Kim, and J. Vomlel: Soft Evidential Update for Multiagent Systems, International Journal of Approximate Reasoning, Volume 29, Issue 1, January 2002, pp. 71-106. (an almost final draft)
[2001]	F. V. Jensen, U. Kjaerulff, B. Kristiansen, H. Langseth, C. Skaanning, J. Vomlel & M. Vomlelová: The SACSO methodology for troubleshooting complex systems. Special Issue on AI in Equipment Service, Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AIEDAM), Vol. 15, pp. 321-333, 2001. (an almost final draft)

Publications in Peer Reviewed Conference Proceedings

[2012]	J. Vomlel and P. Tichavský, Computationally efficient probabilistic inference with noisy threshold models based on a CP tensor decomposition. In the Proceedings of the Sixth European Workshop on Probabilistic Graphical Models (PGM 2012), Granada, Spain, September 19-21, pp. 355-362.
[2010]	T. Ottosen and J. Vomlel, All roads lead to Rome - New search methods for optimal triangulations. In the Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM 2010), Helsinki, Finland, September 13-15, pp. 201-208, 2010.
[2010]	T. Ottosen and J. Vomlel, Honour thy neighbour - Clique maintenance in dynamic graphs. In the Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM 2010), Helsinki, Finland, September 13-15, pp. 209-216, 2010.
[2009]	P. Savický and J. Vomlel, Triangulation heuristics for BN2O networks. In C. Sossai and G. Chemello (Eds.): ECSQARU 2009, Springer LNAI 5590, pp. 566–577, 2009. ISBN: 978-3-642-02905-9. Online version available from Springer.
[2008]	J. Vomlel and P. Savický, Arithmetic circuits of the noisy-or models. In the Proceedings of the Fourth European Workshop on Probabilistic Graphical Models (PGM'08), Hirtshals, Denmark, September 17-19, 2008, pp. 297-304. Detailed results and tested models are available here.
[2008]	M. Studený and J. Vomlel, A Geometric Approach to Learning BN Structures. In the Proceedings of the Fourth European Workshop on Probabilistic Graphical Models (PGM'08), Hirtshals, Denmark, September 17-19, 2008, pp. 281-288. An extended version of this paper and a web page related to this paper.
[2006]	P. Savický and J. Vomlel, Tensor rank-one decomposition of probability tables, In the Proceedings of the 11th IPMU conference, Paris, France, July 2-7, 2006, pp. 2292-2299. See the extended version published in Kybernetika.
[2004]	M. Studený and J. Vomlel, Transition between graphical and algebraic representatives of Bayesian network models (an extended version), In Proceeding of the 2nd European Workshop on Probabilistic Graphical Models (PGM'04), Leiden, the Netherlands. See the extended version published in International Journal of Approximate Reasoning.
[2004]	J. Vomlel: Thoughts on belief and model revision with uncertain evidence, Proceedings of the conference Znalosti 2004, Brno, February 2004, pp. 126-137. See the extended version published in Neural Network World, International Journal on Neural and Mass-Parallel Computing and Information Systems.
[2003]	J. Vomlel: Noisy-or classifier, Proceedings of the 6th Workshop on Uncertainty Processing (WUPES 2003), Hejnice, September 2003, pp. 291-302. See the extended version published in International Journal of Intelligent Systems.
[2003]	J. Vomlel: Integrating inconsistent data in a probabilistic model, Proceedings of the Uncertainty, Incompleteness, Imprecision and Conflict in Multiple Data Sources, an affiliate workshop to ECSQARU'03, Aalborg, 2003. See the extended version published in Journal of Applied Non-Classical Logics.
[2003]	J. Vomlel: Two applications of Bayesian networks, In Proceedings of conference Znalosti 2003 February 2003, Ostrava, Czech Republic, pp. 73-82. K dispozici je i ceska verze. See the extended version published in Kybernetika.
[2002]	J. Vomlel: Bayesian Networks in Educational Testing, In Proceedings of the First European Workshop on Probabilistic Graphical Models (PGM'02), November 6-8, 2002, Cuenca, Spain, pp. 176-185. See the extended version published in International Journal of Uncertainty, Fuzziness and Knowledge Based Systems.
[2002]	J. Vomlel: Exploiting Functional Dependence in Bayesian Network Inference, In Proceedings of The 18th Conference on Uncertainty in Artificial Intelligence (UAI 2002), August 1-4, 2002, University of Alberta, Edmonton, Canada, pp. 528-535.
[2001]	J. Vomlel and C. Skaanning: Troubleshooting with Simultaneous Models. In: S. Benferhat, P. Besnard (Eds.): Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 6th European Conference, ECSQARU 2001, Toulouse, France, September 19-21, 2001, Proceedings. On line version available from Springer, and an almost final draft.

Other Publications

[2012]	J. Vomlel, H. Kružík, P. Tůma, J. Přeček, and M. Hutyra. Machine Learning Methods for Mortality Prediction in Patients with ST Elevation Myocardial Infarction. In the Proceedings of The Nineth Workshop on Uncertainty Processing WUPES'12, Mariánské Lázně, Czech Republic, September 12-15th, 2012, pp. 204-213.
[2011]	V. Kratochvíl, H. Kružík, P. Tůma, J. Vomlel a P. Somol. Predikce hospitalizační mortality u akutního infarktu myokardu. (In Czech). Sborník příspěvků konference MEDSOFT 2011, str. 128-138.
[2009]	M. Studený and J. Vomlel. On open questions in the geometric approach to learning BN structures. In the proceedings of The Eighth Workshop on Uncertainty Processing WUPES'09, Liblice, Czech Republic, September 19-23th, 2009, pp. 226-236.
[2009]	J. Vomlel and P. Savický. An experimental comparison of triangulation heuristics on transformed BN2O networks. In the proceedings of The Eighth Workshop on Uncertainty Processing WUPES'09, Liblice, Czech Republic, September 19-23th, 2009, pp. 251-260.
[2009]	M. Vomlelová and J. Vomlel. Applying Bayesian networks in the game of Minesweeper. In the Proceedings of the Twelfth Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Litomyšl, Czech Republic, September, 2009, pp. 153-162.
[2007]	J. Vomlel and M. Studený. Using imsets for learning Bayesian networks. In the Proceedings of the Tenth Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Liblice, Czech Republic, September, 2007, pp. 178-189.
[2007]	R. Jiroušek, V. Kratochvíl, T. Kroupa, R. Lněnička, M. Studený, J. Vomlel, P. Hampl, and H. Hamplová, An evaluation of string similarity measures on pricelists of computer components. In the Proceedings of the Tenth Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Liblice, Czech Republic, September, 2007, pp. 69-74.
[2006]	M. Studený and J. Vomlel (Editors). Proceedings of the third European Workshop on Probabilistic Graphical Models (PGM'06). Prague, September 12-15, 2006.
[2005]	J. Vomlel, Decomposition of Probability Tables Representing Boolean Functions. In the Proceedings of the Eighth Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Trest, Czech Republic, September, 18 - 21, 2005.
[2005]	P. Savický, J. Vomlel, Tensor rank-one decomposition of probability tables. Research report, DAR-UTIA 2005/26, Praha (an extended version of the IPMU 2006 paper containing a brief description of a numerical algorithm for finding tensor-rank one decompositions).
[2004]	J. Vomlel, Bayesian networks in Mastermind, Proceeding of the 7th Czech-Japan Seminar, Awaji Island, Japan.
[2000]	M. Sochorová and J. Vomlel: Troubleshooting: NP-hardness and solution methods, The Fifth Workshop on Uncertainty Processing WUPES 2000, Jindrichuv Hradec, Czech Republic, 20-24th June 2000. See the extended version published in Soft Computing Journal.
[1999]	J. Vomlel: Methods of Probabilistic Knowledge Integration (PhD Thesis) and the abstract.
[1997]	J. Vomlel: Statistical Methods for Probabilistic Model Parameter Estimation from Incomplete Data and their Application to the Marginal Problem, In: Proc. of WUPES'97, pp. 184-193, January 1997, Prague.
[1996]	J. Vomlel: Dependency Models, Draft Paper, Institute of Information Theory and Automation, 1996, Prague.
[1995]	J. Vomlel: Probabilistic models in Artificial Intelligence, Research Report, Czech Technical University, 1995, Prague.
[1994]	R. Jiroušek and J. Vomlel: Inconsistent knowledge integration in a probabilistic model, In: Proc. of Workshop Mathematical Models for handling partial knowledge in A.I., pp. 263-270, Plenum Publ. Corp., 1994, Erice, Sicily.

Software and datasets

[2008]	A set consisting of 9 Bayesian networks of the bn2o type used in the probabilistic reasoning evaluation at UAI'08.
[2007]	imset.R - a suite of functions for R (implementing also a learning algorithm for Bayesian networks)
[2006]	The Reuters dataset preprocessed by G. Karciauskas

Presentations

[2012]	Computationally efficient probabilistic inference with noisy threshold models based on a CP tensor decomposition. Presentation at the Sixth European Workshop on Probabilistic Graphical Models (PGM 2012), Granada, Spain.
[2012]	Machine Learning Methods for Mortality Prediction in Patients with ST Elevation Myocardial Infarction. Presentation at the Nineth Workshop on Uncertainty Processing WUPES'12, Mariánské Lázně, Czech Republic.
[2011]	Rank of tensors of l-out-of-k functions: an application in probabilistic inference. Presentation at the DAR conference at Marianska, Jachymov, Czech Republic.
[2011]	Predikce hospitalizační mortality u akutního infarktu myokardu. Prezentace na konferenci MEDSOFT 2011, Roztoky u Prahy.
[2010]	Noisy logical connectives in Bayesian networks. Presentation at the Dipleap workshop in Vienna organized within the framework of the ESF/Eurocores program LogICCC.
[2010]	Causal Semantics of Bayesian Networks. Presentation at Probnet 2010 workshop in Salzburg.
[2008]	Jádro koaliční hry - algoritmy. Prezentace na semináři skupiny IS ČSKI a projektu DAR v ÚTIA.
[2008]	Arithmetic Circuits of the Noisy-Or Models. Presentation at the Fourth European Workshop on Probabilistic Graphical Models (PGM'08), Hirtshals, Denmark, September 17-19, 2008.
[2008]	Tensor rank-one decomposition of noisy-or models. Presentation at Alsovice seminar, held in Rakvice, Czech Republic, June, 2008.
[2007]	Using imsets for learning Bayesian networks. Presentation at the Tenth Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Liblice, Czech Republic, September, 2007.
[2007]	An evaluation of string similarity measures on pricelists of computer components. Presentation at the Tenth Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Liblice, Czech Republic, September, 2007.
[2006]	Rank-one decomposistion of probability tables. Presentation at WUPES'06 - the 7th Workshop on Uncertainty Processing held in Mikulov, Czech Republic.
[2006]	Tensor rank-one decomposition of probability tables. Presentation at the 11th IPMU conference in Paris.
[2005]	A variational method for the Rasch model. Presentation at the Czech-Austrian workshop PROBNET 2005.
[2005]	What are imsets and what they are good for. Presentation at VRSR 2005 seminar in Ricky v Orlickych horach.
[2005]	Metody pro zpracovani strukturovaneho textu: porovnavani ceniku. Prednaska na 2. konferenci vyzkumneho centra DAR.
[2005]	Bayesian networks in educational testing. My presentation at Nijmeegs instituut voor informatica en informatiekunde colloquium, Radboud University Nijmegen, Netherlands.
[2005]	Bayesian networks in educational testing. My presentation at the research seminar Quantitative Methods at the Department of Psychology, Catholic University Leuven.
[2005]	Klasifikace metodou logisticke regrese. Prednaska v ramci predmetu Strojove uceni na MFF UK.
[2005]	Applikace bayesovskych siti. Prednaska na seminari kvantitativni metodologie na FTVS UK.
[2005]	Some applications of Bayesian networks. My presentation at a seminar of the Czech Society for Cybernetics and Informatics (CSKI). A paper-saving PostScript version to print.
[2004]	Integrating inconsistent data in a probabilistic model. My presentation at Salzburg 2004 workshop and a paper-saving PostScript version to print.
[2004]	Probabilistic reasoning with uncertain evidence, My presentation for Working Group on Theoretical Robotics of the Czech Society for Cybernetics and Informatics (CSKI) A paper-saving PostScript version to print.
[2004]	Implementation of Imsets in the R language (a short presentation after Milan Studeny's talk at PGM'04).
[2004]	Uvod do Bayesovskych siti, prednaska v ramci predmetu Medicinska informatika. K dispozici je i PostScriptova verze pro tisk.
[2004]	Bayesian networks in Mastermind, my presentation at the 7th Czech-Japan Seminar, Awaji Island, Japan. A paper-saving PostScript version to print.
[2004]	Thoughts on belief and model revision with uncertain evidence, my presentation at conference Znalosti 2004. A paper-saving PostScript version to print.
[2003]	Noisy-or classifier, my presentation at WUPES 2003. A paper-saving PostScript version to print.
[2003]	Integrating inconsistent data in a probabilistic model, my presentation at an affiliate workshop to ECSQARU 2003 "Uncertainty, Incompleteness, Imprecision and Conflict in Multiple Data Sources". A paper-saving PostScript version to print.
[2003]	Two applications of Bayesian networks My presentation for Working Group on Theoretical Robotics of the Czech Society for Cybernetics and Informatics (CSKI). A paper-saving PostScript version to print. My presentation for students from Nederlands in UTIA in April 2003. A paper-saving PostScript version to print. My presentation at conference Znalosti 2003 held in February 2003 in Ostrava, Czech Republic. A paper-saving PostScript version to print.
[2002]	Bayesian Networks in Educational Testing My presentation at the PGM'02 workshop and a paper-saving PostScript version to print. My presentation within the LISP seminar series and a paper-saving PostScript version to print.
[2002]	Visualizing and Exploring Data (my presentation within Aalborg BSS data mining tutorial series).
[2002]	Exploiting Functional Dependence in Bayesian Network Inference My presentation within the LISP seminar series and a paper-saving PostScript version to print My presentation at the Salzburg workshop and a paper-saving PostScript version to print Efficient Propagation for Computerized Adaptive Testing (my presentation within the Aalborg BSS seminar series).
[2001]	Troubleshooting with Simultaneous Models, Symbolic and Quantitative Approaches to Reasoning with Uncertainty 6th European Conference, ECSQARU 2001, Toulouse, France, September 19-21.
[2001]	Game Networks (my presentation within Aalborg BSS seminar series) based mainly on the UAI'2000 paper "Game Networks by Piero La Mura".
[2000]	Markov Games (my presentation within the series of BSS workshops on E-services) based on papers Michael L. Littman: Markov Games as a framework for multiagent reinforcement learning, Proceedings of ICML'94, pages 157-163 and Junling Hu and Michael P. Wellman: Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm, Proceedings of ICML'98, pages 242-250
[2000]	Methods of Probabilistic Knowledge Integration (overheads from the defence of my PhD Thesis).
[2000]	Troubleshooting: NP-hardness and solution methods, The Fifth Workshop on Uncertainty Processing WUPES'2000, Jindrichuv Hradec, Czech Republic, 20-24th June 2000.
[1999]	Iterative Knowledge Integration, overheads from my lecture within LISp seminar

Teaching

Temata diplomovych praci

[2011] Přednáška Příklady aplikací bayesovských sítí v rámci předmětu 4IZ410 - Teorie informace a inference na VŠE Praha.

[2010] Přednáška Inference v bayesovských sítích a Aplikace bayesovských sítí, v rámci předmětu PRAVDĚPODOBNOSTNÍ MODELY UMĚLÉ INTELIGENCE, Fakulta jaderná a fyzikálně inženýrská, České vysoké učení technické v Praze.

[2010,
2009] Přednáška "Úvod do bayesovských sítí" v rámci kurzu "Počítačová podpora diagnostiky a terapie".
Soubory wet_grass.net, two_coins_1.net, two_coins_2.net, asia.net a monty_hall.net pro spuštění v programu Hugin Lite.

[2008] Přednáška "Úvod do bayesovských sítí" v rámci kurzu "Počítačová podpora diagnostiky a terapie".

[2007]
Postgraduate course at UNED in Madrid, Spain
for a detailed programme see this page:

Inference with Bayesian networks (PDF of the presentation):

Classification (PDF of the presenation):

Learning Bayesian networks: (PDF of the presentation on score based learning and PDF of the presentation of EM-algorithm (slides of F.V. Jensen and T.D. Nielsen ))

Decision-theoretic troubleshooting (PDF of the presentation)

Computerized adaptive testing (CAT) using Bayesian networks (PDF of the presentation)

[2004]
Principy inteligentnich systemu (IZI454),

University of Economics, Prague, Czech Republic

Based on the manuscript Metody reprezentace a zpracovani znalosti v umele inteligenci by Radim Jirousek.

Geneticke algoritmy, usporna verze pro tisk a ukazkovy program prevzaty z www.codeproject.com .

Linearni rozhodovaci funkce. Kapitola 3 knihy Metody reprezentace a zpracovani znalosti v umele inteligenci.

Chyba rozhodovani, usporna verze pro tisk. Ukazkovy system pro vizulizaci dat (Ggobi) je k dispozici na www.ggobi.org .

Uvod do bayesovskych siti , usporna verze pro tisk a ukazka rozhodovaciho diagramu ve formatu Hugin NET.

Pouziti bayesovskych siti pro testovani znalosti a usporna verze pro tisk.

Technicka diagnostika a usporna verze pro tisk

[2004] Managing uncertainty in Artficial Intelligence (Zpracovani nejistoty v umele inteligenci, IZI462), University of Economics, Prague. Advertising poster.

[2002] Aalborg University, Denmark: DAT6/KDE4: M.Sc. project supervisor

[2001] Aalborg University, Denmark: KDE1 - Knowledge and Data Engineering: project supervisor
Aalborg University, Denmark: DAT5/KDE3 - Knowledge and Data Engineering: project supervisor and lecturer

Approximate propagation in Bayesian networks, my lecture within DAT5 course at Aalborg University.

Learning parameters of Bayesian Networks, my lecture within DAT5 course at Aalborg University.

[2000] Aalborg University, Denmark: KDE - Knowledge and Data Engineering: project supervisor

[1999] Aalborg University, Denmark: DAT3 - Decision Support Systems 1: project supervisor (info in Danish)

[1998] University of Economics, Prague, Czech Republic: EKO 414 - Optimization Methods (in Czech)

Miscellaneous

A cooperative Learning Game
Crumple my photo
Monty Hall Puzzle (an example of a simple Bayesian network model from Hugin) - a jeho verze v češtině
Example of the weaknesses of traditional reasoning for risk assessment (an example of a Bayesian network model for risk assesment from Agena)
Finding The Card - a card trick based on a form of contraction mapping theorem
A puzzle archive
Mastermind
Interactive Mathematics Miscellany and Puzzles
Clean your screen!
Objednejte se na vysetreni do kardiologicke ambulance EuroMISE centra (zdarma tu ziskate cenne informace o Vasem riziku aterosklerozy a pomuzete tim i vyzkumu v teto oblasti). I am a member of the municipal board of Světice

Temata diplomovych praci

[2011]	Přednáška Příklady aplikací bayesovských sítí v rámci předmětu 4IZ410 - Teorie informace a inference na VŠE Praha.
[2010]	Přednáška Inference v bayesovských sítích a Aplikace bayesovských sítí, v rámci předmětu PRAVDĚPODOBNOSTNÍ MODELY UMĚLÉ INTELIGENCE, Fakulta jaderná a fyzikálně inženýrská, České vysoké učení technické v Praze.
[2010, 2009]	Přednáška "Úvod do bayesovských sítí" v rámci kurzu "Počítačová podpora diagnostiky a terapie". Soubory wet_grass.net, two_coins_1.net, two_coins_2.net, asia.net a monty_hall.net pro spuštění v programu Hugin Lite.
[2008]	Přednáška "Úvod do bayesovských sítí" v rámci kurzu "Počítačová podpora diagnostiky a terapie".
[2007]	Postgraduate course at UNED in Madrid, Spain for a detailed programme see this page: Inference with Bayesian networks (PDF of the presentation): Classification (PDF of the presenation): Learning Bayesian networks: (PDF of the presentation on score based learning and PDF of the presentation of EM-algorithm (slides of F.V. Jensen and T.D. Nielsen )) Decision-theoretic troubleshooting (PDF of the presentation) Computerized adaptive testing (CAT) using Bayesian networks (PDF of the presentation)
[2004]	Principy inteligentnich systemu (IZI454), University of Economics, Prague, Czech Republic Based on the manuscript Metody reprezentace a zpracovani znalosti v umele inteligenci by Radim Jirousek. Geneticke algoritmy, usporna verze pro tisk a ukazkovy program prevzaty z www.codeproject.com . Linearni rozhodovaci funkce. Kapitola 3 knihy Metody reprezentace a zpracovani znalosti v umele inteligenci. Chyba rozhodovani, usporna verze pro tisk. Ukazkovy system pro vizulizaci dat (Ggobi) je k dispozici na www.ggobi.org . Uvod do bayesovskych siti , usporna verze pro tisk a ukazka rozhodovaciho diagramu ve formatu Hugin NET. Pouziti bayesovskych siti pro testovani znalosti a usporna verze pro tisk. Technicka diagnostika a usporna verze pro tisk
[2004]	Managing uncertainty in Artficial Intelligence (Zpracovani nejistoty v umele inteligenci, IZI462), University of Economics, Prague. Advertising poster.
[2002]	Aalborg University, Denmark: DAT6/KDE4: M.Sc. project supervisor
[2001]	Aalborg University, Denmark: KDE1 - Knowledge and Data Engineering: project supervisor Aalborg University, Denmark: DAT5/KDE3 - Knowledge and Data Engineering: project supervisor and lecturer Approximate propagation in Bayesian networks, my lecture within DAT5 course at Aalborg University. Learning parameters of Bayesian Networks, my lecture within DAT5 course at Aalborg University.
[2000]	Aalborg University, Denmark: KDE - Knowledge and Data Engineering: project supervisor
[1999]	Aalborg University, Denmark: DAT3 - Decision Support Systems 1: project supervisor (info in Danish)
[1998]	University of Economics, Prague, Czech Republic: EKO 414 - Optimization Methods (in Czech)