RNDr. Milan Studený, DrSc.

senior research fellow

Milan Studený
studeny@utia.cas.cz 266052304 Personal web
Department: Department of Decision-Making Theory
Research interests: Probabilistic conditional independence structures, conditional independence in context uncertainty calculi in AI, graphical statistical models (Bayesian networks, chain graphs), methods of polyhedral geometry in coalitional game theory, information-theoretical inequalities for entropic function (study of the entropic region), algebraic statistics.

Biography

Publication list

Education

  • (1976 - 1981) graduate diploma, Charles University, Faculty of Mathematics and Physics, Prague.
    Thesis topic: The differentiation of measures in metric spaces. (in Czech, under guidance of David Preiss).
  • (1982 - 1983) stay at university, Charles University, Faculty of Mathematics and Physics, Prague. Research in real analysis under guidance of David Preiss.
  • (1983 - 1986) doctoral studies (for CSc. degree), specialization: theoretical cybernetics. Czechoslovak Academy of Sciences, Institute of Information Theory and Automation, Prague. Thesis topic: The notion of multiinformation in probabilistic decision making (in Czech, under guidance of Albert Perez).
  • (2001) DrSc. degree, specialization: mathematical informatics and theoretical cybernetics.
    Academy of Sciences of the Czech Republic. Thesis topic: On mathematical description of probabilistic conditional independence structures.

 

Employment

  • (1982 - 1983) stay at Charles University, see above.
  • (1983 - 1986) doctoral studies, see above.
  • (1987 - 1991) research worker, Czechoslovak Academy of Sciences, Institute of Information Theory and Automation (ÚTIA), Czechoslovakia.
  • (1996 - 2000) partially, external research worker, University of Economics, Prague, Faculty of Informatics and Statistics, Laboratory of Intelligent Systems, Prague, Czech Republic.
  • (1991 - present) senior research worker, Academy of Sciences of the Czech Republic, ÚTIA, Department of Decision-Making Theory (MTR), Czech Republic.
  • (2003 - 2004) head of MTR, ÚTIA, Czech Republic.

 

Research projects lead in the role of PI

  • Conditional independence properties in uncertainty processing. Internal grant n. 275105 of Academy of Sciences of the Czech Republic (1993–1995).
  • (in the role of co-PI) Marginal problem and its applications. Grant n. 201/94/0471 of the Grant Agency of the Czech Republic (1994–1996).
  • Conditional independence structures: information theoretical approach. Grant n. 201/98/0478 of the Grant Agency of the Czech Republic (1998).
  • Conditional independence structures: information theoretical approach II. Grant n. 201/01/1482 of the Grant Agency of the Czech Republic (2001–2003).
  • Conditional independence structures: information theoretical approach III. Grant n. 201/04/0393 of the Grant Agency of the Czech Republic (2004–2006).
  • Conditional independence structures: graphical and algebraic approaches. Grant n. 201/08/0539 of the Grant Agency of the Czech Republic (2008–2012).
  • Conditional independence structures: algebraic and geometric methods. Grant n. 13-20012S of the Czech Science Foundation (new name for the Grant Agency of the Czech Republic) (2013–2015).
  • Conditional independence structures: combinatorial and optimization methods. Grant n. 16-12010S of the Czech Science Foundation (2016–2018).
  • Conditional independence structures: methods of polyhedral geometry. Grant n. 19-04579S of the Czech Science Foundation (2019–2021).

 

Educational activities (in cooperation with either Charles University or Czech Technical University in Prague):

  • supervisor of a PhD student Petr Šimeček (2004–2006). Thesis title: Graphical models and conditional independence structures (in Czech). Charles University, Faculty of Mathematics and Physics. Defended in September 2007.
  • supervisor of diploma student J. Fontán. Thesis title: Conditional independence structures in directed graphs (in Czech). Czech Technical University in Prague, Faculty of Nuclear Science and Physical Engineering, 1996.
  • supervisor of diploma student M. Volf. Thesis title: Independency models induced by chain graphs. (in Czech). Czech Technical University in Prague, Faculty of Nuclear Science and Physical Engineering, 1998.
  • supervisor of diploma student Š. Štěpánová. Thesis title: Equivalence of chain graphs (in Czech). Charles University, Faculty of Mathematics and Physics, Prague 2003.
  • supervisor of diploma student E. Beljayeva. Thesis title: Annotated graphs and Bayesian networks. Charles University, Faculty of Mathematics and Physics, Prague 2015.
  • supervisor of a bachelor student J. Zouhar. Thesis title: Recursive linear models and conditional independence structures (in Czech). Charles University, Faculty of Mathematics and Physics, Prague 2010.
  • lecturing an optional one-term course "Conditional Independence Structures" for MSc students. Charles University, Faculty of Mathematics and Physics, Prague (since 2003 until now, sometimes in English)
  • supervising "Seminar on Probability for PhD students I." Charles University, Faculty of Mathematics and Physics, Prague (autumn 2012, autumn 2016)
  • mentor of a PhD student Vera Djordjilovič from Padua University, Italy during her stay at Institute of Information Theory and Automation (August–December 2013, October 2014)
  • external examiner of PhD thesis (K. Sadeghi), Oxford University, UK (January 2012)

  • reviewer of PhD thesis (T. Boege), Otto-von-Guericke-Universität Magdeburg, Germany (April 2022)

     

ORCID link 

 

More details on publications and organizational activities can be found on the personal web (see the link above).

Books and chapters

  1. Studený Milan: Conditional Independence and Basic Markov Properties, Handbook of Graphical Models, p. 3-38, Eds: Maathuis Marloes, Drton Mathias, Lauritzen Steffen, Wainwright Martin Download [2018]
  2. Haws D., Cussens J., Studený Milan: Polyhedral approaches to learning Bayesian networks, Algebraic and Geometric Methods in Discrete Mathematics, p. 155-188, Eds: Harrington H. A., Omar M., Wright M. DOI: 10.1090/conm/685/13751 [2017]
  3. Vomlel Jiří, Studený Milan: Graphical and Algebraic Representatives of Conditional Independence Models, Advances in Probabilistic Graphical Models, p. 55-80, Eds: Lucas Peter, Gámez José A., Salmerón Antonio [2007]
  4. Studený Milan: Probabilistic Conditional Independence Structures, Springer (London, 2005) [2005]
  5. Studený Milan: Other approaches to the description of conditional independence structures, Highly Structured Stochastic Systems, p. 106-108, Eds: Green P. J., Hjort N. L., Richardson S., Oxford University Press (New York, 2003) [2003]
  6. Studený Milan, Vejnarová Jiřina: On multiinformation function as a tool for measuring stochastic dependence, Learning in Graphical Models, p. 261-297, Kluwer Academic (Dordrecht, 1998) [1998]
  7. Studený Milan: Description of Conditional Independence Structures by Means of Imsets: A Connection with Product Formula Validity, Uncertainty in Intelligent Systems, p. 179-194, Eds: Bouchon-Meunier B., Valverde L., Yager R. R., Elsevier (Amsterdam, 1993) [1993]

Journal articles

  1. Boege T., Bolt J. H., Studený Milan: Self-adhesivity in lattices of abstract conditional independence models, Discrete Applied Mathematics 361 1 (2025), p. 196-225 Download Download DOI: 10.1016/j.dam.2024.10.006 [2025]
  2. Studený Milan, Kratochvíl Václav: Facets of the cone of exact games, Mathematical Methods of Operations Research 95 1 (2022), p. 35-80 Download Download DOI: 10.1007/s00186-022-00770-4 [2022]
  3. Studený Milan: Conditional independence structures over four discrete random variables revisited: conditional Ingleton inequalities, IEEE Transactions on Information Theory 67 11 (2021), p. 7030-7049 Download Download DOI: 10.1109/TIT.2021.3104250 [2021]
  4. Studený Milan, Cussens J., Kratochvíl Václav: The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture, International Journal of Approximate Reasoning 138 1 (2021), p. 188-203 Download Download DOI: 10.1016/j.ijar.2021.07.014 [2021]
  5. Studený Milan: Contribution of František Matúš to the research on conditional independence, Kybernetika 56 5 (2020), p. 850-874 Download Download DOI: 10.14736/kyb-2020-5-0850 [2020]
  6. Kroupa Tomáš, Studený Milan: Facets of the cone of totally balanced games, Mathematical Methods of Operations Research 90 2 (2019), p. 271-300 Download Download DOI: 10.1007/s00186-019-00672-y [2019]
  7. Studený Milan, Kratochvíl Václav: Linear criterion for testing the extremity of an exact game based on its finest min-representation, International Journal of Approximate Reasoning 101 1 (2018), p. 49-68 Download DOI: 10.1016/j.ijar.2018.06.007 [2018]
  8. Studený Milan, Cussens J.: Towards using the chordal graph polytope in learning decomposable models, International Journal of Approximate Reasoning 88 1 (2017), p. 259-281 Download DOI: 10.1016/j.ijar.2017.06.001 [2017]
  9. Cussens J., Haws D., Studený Milan: Polyhedral aspects of score equivalence in Bayesian network structure learning, Mathematical Programming 164, p. 285-324 Download DOI: 10.1007/s10107-016-1087-2 [2017]
  10. Studený Milan, Kroupa Tomáš: Core-based criterion for extreme supermodular functions, Discrete Applied Mathematics 206 1 (2016), p. 122-151 Download DOI: 10.1016/j.dam.2016.01.019 [2016]
  11. Tanaka K., Studený Milan, Takemura A., Sei T.: A linear-algebraic tool for conditional independence inference, Journal of Algebraic Statistics 6 2 (2015), p. 150-167 Download DOI: 10.18409/jas.v6i2.46 [2015]
  12. Studený Milan, Haws D.: Learning Bayesian network structure: towards the essential graph by integer linear programming tools, International Journal of Approximate Reasoning 55 4 (2014), p. 1043-1071 Download DOI: 10.1016/j.ijar.2013.09.016 [2014]
  13. Studený Milan, Haws D.C.: On polyhedral approximations of polytopes for learning Bayesian networks, Journal of Algebraic Statistics 4 1 (2013), p. 59-92 Download [2013]
  14. Hemmecke R., Lindner S., Studený Milan: Characteristic imsets for learning Bayesian network structure, International Journal of Approximate Reasoning 53 9 (2012), p. 1336-1349 Download DOI: 10.1016/j.ijar.2012.04.001 [2012]
  15. Studený Milan, Vomlel Jiří: On open questions in the geometric approach to structural learning Bayesian nets, International Journal of Approximate Reasoning 52 5 (2011), p. 627-640 Download DOI: 10.1016/j.ijar.2010.09.004 [2011]
  16. Bouckaert R., Hemmecke R., Lindner S., Studený Milan: Efficient algorithms for conditional independence inference, Journal of Machine Learning Research 11 1 (2010), p. 3453-3479 Download [2010]
  17. Studený Milan, Vomlel Jiří, Hemmecke R.: A geometric view on learning Bayesian network structures, International Journal of Approximate Reasoning 51 5 (2010), p. 578-586 Download DOI: 10.1016/j.ijar.2010.01.014 [2010]
  18. Studený Milan, Roverato A., Štěpánová Š.: Two operations of merging and splitting components in a chain graph, Kybernetika 45 2 (2009), p. 208-248 Download [2009]
  19. Studený Milan, Vomlel Jiří: A reconstruction algorithm for the essential graph, International Journal of Approximate Reasoning 50 2 (2009), p. 385-413 Download DOI: 10.1016/j.ijar.2008.09.001 [2009]
  20. Perez A., Studený Milan: Comparison of two methods for approximation of probability distributions with prescribed marginals, Kybernetika 43 5 (2007), p. 591-618 Download [2007]
  21. Bouckaert R. R., Studený Milan: Racing algorithms for conditional independence inference, International Journal of Approximate Reasoning 45 2 (2007), p. 386-401 Download [2007]
  22. Roverato A., Studený Milan: A graphical representation of equivalence classes of AMP chain graphs, Journal of Machine Learning Research 7 6 (2006), p. 1045-1078 Download [2006]
  23. Studený Milan: Characterization of inclusion neighbourhood in terms of the essential graph, International Journal of Approximate Reasoning 38 3 (2005), p. 283-309 Download [2005]
  24. Studený Milan: Characterization of essential graphs by means of the operation of legal merging of components, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems 12, p. 43-62 [2004]
  25. Studený Milan: Chain graph models and their causal interpretations - discussion on the paper by Lauritzen and Richardson, Journal of the Royal Statistical Society Series B-Statistical Methodology 64 3 (2002), p. 358 [2002]
  26. Studený Milan: On stochastic conditional independence: the problems of characterization and description, Annals of Mathematics and Artificial Intelligence 35, p. 323-341 [2002]
  27. Paz A., Geva R. Y., Studený Milan: Representation of irrelevance relations by annotated graphs, Fundamenta Informaticae 42 1 (2000), p. 149-199 [2000]
  28. Volf M., Studený Milan: A graphical characterization of the largest chain graphs, International Journal of Approximate Reasoning 20 3 (1999), p. 209-236 [1999]
  29. Studený Milan, Bouckaert R. R.: On chain graph models for description of conditional independence structures, Annals of Statistics 26 4 (1998), p. 1434-1495 [1998]
  30. Studený Milan: A recovery algorithm for chain graphs, International Journal of Approximate Reasoning 17 213 (1997), p. 265-293 [1997]
  31. Studený Milan: Semigraphoids and structures of probabilistic conditional independence, Annals of Mathematics and Artificial Intelligence 21 1 (1997), p. 71-98 [1997]
  32. Zvárová Jana, Studený Milan: Information-theoretic Approach to Constitution and Reduction of Medical Data, International Journal of Medical Informatics 45, p. 65-74 DOI: 10.1016/S1386-5056(97)00036-1 [1997]
  33. Matúš František, Studený Milan: Conditional independences among four random variables I, Combinatorics, Probability and Computing 4, p. 269-278 [1995]
  34. Studený Milan: Description of structures of stochastic conditional independence by means of faces and imsets. 2nd part: basic theory. , International Journal of General Systems 23 3 (1995), p. 201-219 [1995]
  35. Studený Milan: Description of structures of stochastic conditional independence by means of faces and imsets. 3rd part: examples of use and appendices, International Journal of General Systems 23 4 (1995), p. 323-341 [1995]
  36. Studený Milan: Conditional independence and natural conditional functions, International Journal of Approximate Reasoning 12 1 (1995), p. 43-68 [1995]
  37. Studený Milan: Description of structures of stochastic conditional independence by means of faces and imsets. 1st part: introduction and basic concepts, International Journal of General Systems 23 2 (1994), p. 123-137 [1994]
  38. Studený Milan: Structural semigraphoids, International Journal of General Systems 22 2 (1994), p. 207-217 [1994]
  39. Lachout Petr, Studený Milan, Šindelář Jan: On set-valued measures, Informatica 4, p. 21-44 [1993]
  40. Studený Milan: Convex Cones in Finite-Dimensional Real Vector Spaces, Kybernetika 29 2 (1993), p. 180-200 [1993]
  41. Malvestuto F. M., Studený Milan: Comment on "A Unique Formal System for Binary Decompositions of Database Relations, Probability Distributions, and Graphs", Information Sciences 63, p. 1-2 [1992]
  42. Studený Milan: Multiinformation and the Problem of Characterization of Conditional Independence Relations, Problems of Control and Information Theory 18 1 (1989), p. 3-16 [1989]
  43. Studený Milan: Attempts at Axiomatic Description of Conditional Independence, Kybernetika 25 3 (1989), p. 72-79 [1989]

Other publications

  1. Studený Milan: On combinatorial descriptions of faces of the cone of supermodular functions, UTIA AV CR (Praha, 2024) Download Download [2024]
  2. Studený Milan, Cussens J., Kratochvíl Václav: Dual formulation of the chordal graph conjecture, Proceedings of Machine Learning Research, Volume 138: International Conference on Probabilistic Graphical Models, 23-25 September 2020, Hotel Comwell Rebild Bakker, Skørping, Denmark, p. 449-460, Eds: Nielsen T. D., Jaeger M. Download [2021]
  3. Studený Milan, Kratochvíl Václav, Vomlel Jiří: On irreducible min-balanced set systems, Symbolic and Quantitative Approaches to Reasoning with Uncertainty : 15th European Conference, ECSQARU 2019, Belgrade, Serbia, September 18-20, 2019, p. 444-454, Eds: Kern-Isberner G., Ognjanovic Z. Download DOI: 10.1007/978-3-030-29765-7_37 [2019]
  4. Studený Milan, Kroupa Tomáš, Kratochvíl Václav: On attempts to characterize facet-defining inequalities of the cone of exact games, Proceedings of the 11th Workshop on Uncertainty Processing (WUPES’18), p. 177-187, Eds: Kratochvíl Václav, Vejnarová Jiřina Download [2018]
  5. Studený Milan, Kratochvíl Václav: Linear core-based criterion for testing extreme exact games, Proceedings of the 10th International Symposium on Imprecise Probability: Theories and Applications, p. 313-324, Eds: Antonucci A., Corani G., Couso I., Destercke S. Download [2017]
  6. Studený Milan: Basic facts concerning extreme supermodular functions, ÚTIA AV ČR v.v.i (Praha, 2016) Download [2016]
  7. Studený Milan, Cussens J.: The chordal graph polytope for learning decomposable models, Proceedings of the Eighth International Conference on Probabilistic Graphical Models, p. 499-510, Eds: Antonucci A., Corani G., Polpo de Campos C. Download DOI: 10.1016/j.ijar.2017.06.001 [2016]
  8. Studený Milan: How matroids occur in the context of learning Bayesian network structure, Uncertainty in Artificial Intelligence, Proceedings of the Thirty-First Conference (2015), p. 832-841 Download [2015]
  9. Studený Milan: Integer linear programming approach to learning Bayesian network structure: towards the essential graph, Proceedings of the 6th European Workshop on Graphical Models, p. 307-314 Download [2012]
  10. Studený Milan: LP relaxations and pruning for characteristic imsets, ÚTIA AVČR (Praha, 2012) Download [2012]
  11. Studený Milan, Haws D., Hemmecke R., Lindner S.: Polyhedral approach to statistical learning graphical models, Harmony of Gröbner Bases and the Modern Industrial Society, p. 346-372 Download DOI: 10.1142/9789814383462_0020 [2012]
  12. Studený Milan, Haws D.: On polyhedral approximations of polytopes for learning Bayes nets, ÚTIA AV ČR (Praha, 2011) Download [2011]
  13. Studený Milan, Hemmecke R., Lindner S.: Characteristic imset: a simple algebraic representative of a Bayesian network structure, Proceedings of the 5th European Workshop on Probabilistic Graphical Models (PGM 2010), p. 257-264, Eds: Myllymaki Petri, Roos Teemu, Jaakkola Tommi Download [2010]
  14. Studený Milan, Hemmecke R., Vomlel Jiří, Lindner S.: Polyhedral approach to statistical learning graphical models, Abstracts of The 2nd CREST-SBM International Conference on Harmony of Groebner Bases and the Moderm Industrial Socienty, p. 1-4 Download [2010]
  15. Studený Milan, Vomlel Jiří: On open questions in the geometric approach to learning BN structures, WUPES'09, p. 226-236, Eds: Kroupa T., Vejnarová J. Download [2009]
  16. Studený Milan: Mathematical aspects of learning Bayesian networks: Bayesian quality criteria, ÚTIA AV ČR, v.v.i (Praha, 2008) Download [2008]
  17. Studený Milan, Vomlel Jiří: A Geometric Approach to Learning BN Structures, Proceedings of the Fourth European Workshop on Probabilistic Graphical Models (PGM'08), p. 281-288, Eds: Jaeger Manfred, Nielsen Thomas D. Download [2008]
  18. Jiroušek Radim, Kratochvíl Václav, Kroupa Tomáš, Lněnička Radim, Studený Milan, Vomlel Jiří, Hampl P., Hamplová H.: An evaluation of string similarity measures on pricelists of computer components, Proceedings of Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /10./, p. 1-6, Eds: Kroupa T., Vejnarová J. [2007]
  19. Vomlel Jiří, Studený Milan: Using imsets for learning Bayesian networks, Proceedings of Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /10./, p. 178-189, Eds: Kroupa T., Vejnarová J. [2007]
  20. Proceedings of the 3th European Workshop on Probabilistic Graphical Models, Agentura Action M (Praha, 2006) [2006]
  21. Studený Milan: An algeraic approach to structural learning Bayesian networks, IPMU 2006. Information Processing and Management of Uncertainty in Knowledge-Based Systems, p. 2284-2291, Eds: Bouchon-Meunier B., Yager R. R. [2006]
  22. Hamplová H., Ivánek J., Jiroušek Radim, Kroupa Tomáš, Lněnička Radim, Studený Milan, Vomlel Jiří: Decision support system for comparison of price lists, Proceedings of the 8th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, p. 32-38, Eds: Kroupa T., Vejnarová J., Oeconomica (Praha, 2005) [2005]
  23. Bouckaert R. R., Studený Milan: Racing for conditional independence inference, Proceedings of the 8th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty 3571, p. 221-232 [2005]
  24. Perez A., Studený Milan: Comparsion of Two Methods for Approximation of Probability Distributions with Prescribed Marginals, ÚTIA AV ČR (Praha, 2005) [2005]
  25. Studený Milan, Roverato A., Štěpánová Š.: Two Operations of Merging Components in a Chain Graph, ÚTIA AV ČR (Praha, 2005) [2005]
  26. Roverato A., Studený Milan: A Graphical Representation of Equivalence Classes of AMP Chain Graphs, ÚTIA AV ČR (Praha, 2005) [2005]
  27. Šimeček P., Studený Milan: Využití pojmu Hilbertovy báze pro ověřování hypotézy o shodnosti strukturálních a kombinatorických imsetů, Sborník prací 13. letní školy JČMF ROBUST 2004, p. 395-401, Eds: Antoch J., Dohnal G., JČMF (Praha, 2004) [2004]
  28. Studený Milan, Vomlel Jiří: Transition between graphical and algebraic representatives of Bayesian network models, Proceedings of the Second European Workshop on Probabilistic Graphical Models, p. 193-200 [2004]
  29. Studený Milan: Structural imsets: an algebraic method for describing conditional independence structures, Proceedings of the Tenth International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, p. 1323-1330 [2004]
  30. Šimeček Petr, Studený Milan: Využití Hilbertovy báze k ověření shodnosti strukturálních a kombinatorických imsetů, Sborník ROBUST 2004, p. 395-402, Eds: Antoch J., Dohnal G. [2004]
  31. Studený Milan: Characterization of inclusion neighbourhood in terms of the essential graph: Lower neighbours, Proceedings of the 6th Workshop on Uncertainty Processing, p. 243-262, University of Economics (Prague, 2003) [2003]
  32. Studený Milan: Characterization of inclusion neighbourhood in terms of the essential graph: upper neighbours, Symbolic and Quantitative Approaches to Reasoning with Uncertainty. European Conference, p. 161-172, Eds: Nielsen T. D., Zhang N. L., Springer (Berlin, 2003) [2003]
  33. Studený Milan: O použití řetězcových grafů pro popis struktur podmíněné nezávislosti, ROBUST'2002. Sborník prací dvanácté zimní školy JČMF, p. 292-314, Eds: Antoch J., Dohnal G., Klaschka J., JČMF (Praha, 2002) [2002]
  34. Studený Milan: Characterization of essential graphs by means of an operation of legal component merging, Proceedings of the First European Workshop on Probabilistic Graphical Models, p. 161-168, Eds: Gamez J. A., Salmeron A., University of Castilla (Cuenca, 2002) [2002]
  35. Studený Milan: On methods of description of conditional independence structures. Abstract, Abstracts of the 24th European Meeting of Statisticians & 14th Prague Conference on Information Theory, Statistical Decision Functions and Random Processes, p. 333, Eds: Janžura M., Mikosch T., Institute of Information Theory and Automation (Prague, 2002) [2002]
  36. Studený Milan: Algebraic approach to learning Bayesian networks. Abstract, BAYESIAN STATISTICS 7 Programme Abstracts Participants, p. 179, Universitat de Valencia (Valencia, 2002) [2002]
  37. Jiroušek Radim, Studený Milan, Vejnarová Jiřina: Open problems inspired by Albert Perez, Conditionals, Information, Inference, p. 117-128, Eds: Kern-Isberner G., Rodder W., Fern Universität (Hagen, 2002) [2002]
  38. Studený Milan: On non-graphical description of models of conditional independence structure, Katholieke Universiteit (Leuven, 2001) Download [2001]
  39. Kočka T., Bouckaert R. R., Studený Milan: On characterizing inclusion of Bayesian networks, Uncertainty in Artificial Intelligence. Proceeding of the 17th Conference, p. 261-268, Eds: Breese J., Koller D., Morgan Kaufmann (San Francisco, 2001) [2001]
  40. Studený Milan: On Mathematical Description of Probabilistic Conditional Independence Structures. DrSc. Dissertation (2001) [2001]
  41. Kočka T., Bouckaert R. R., Studený Milan: On the Inclusion Problem, ÚTIA AV ČR (Praha, 2001) [2001]
  42. Studený Milan: On stochastic conditional independence: Problem of characterization and description, Partial Knowledge and Uncertainty: Independence, Conditioning, Inference, p. 5-8, Eds: Scozzafava R., Vantaggi B., Baltzer Science Publ. (Rome, 2000) [2000]
  43. Studený Milan, Bouckaert R. R., Kočka T.: Extreme Supermodular Set Functions over Five Variables, ÚTIA AV ČR (Praha, 2000) [2000]
  44. Matúš František, Studený Milan: Workshop on Conditional Independence Structures and Graphical Models. Book of Abstracts, ÚTIA AV ČR (Praha, 1999) [1999]
  45. García-Mata Osvaldo, Studený Milan: About the Closure Operation for Relational Models Induced by Syntactic Inference Rules, ÚTIA AV ČR (Praha, 1999) [1999]
  46. Dawid A. P., Studený Milan: Conditional products: An alternative approach to conditional independence, Artificial Intelligence and Statistics 99. Proceedings, p. 32-40, Eds: Heckerman D., Whittaker J., Morgan Kaufmann (San Francisco, 1999) [1999]
  47. Studený Milan: Complexity of structural models, Prague Stochastics '98. Proceedings, p. 521-528, Eds: Hušková M., Lachout P., Víšek J. Á., JČMF (Praha, 1998) [1998]
  48. Studený Milan: Bayesian networks from the point of view of chain graphs, Uncertainty in Artificial Intelligence. Proceedings of the Fourteenth Conference, p. 496-503, Eds: Cooper G. F., Moral S., Morgan Kaufmann (San Francisco, 1998) [1998]
  49. Studený Milan: Comparison of graphical approaches to description of conditional independence structures, Proceedings of the 4th Workshop on Uncertainty Processing, p. 156-172, VŠE (Praha, 1997) [1997]
  50. Studený Milan: On marginalization, collapsibility and precollapsibility, Distributions with Given Marginals and Moment Problems, p. 191-198, Eds: Beneš V., Štěpán J., Kluwer (Dordrecht, 1997) [1997]
  51. Studený Milan: On separation criterion and recovery algorithm for chain graphs, Uncertainty in Artificial Intelligence. Proceedings, p. 509-516, Eds: Horvik E., Jensen F., Morgan Kaufmann Publ. (San Francisco, 1996) [1996]
  52. Studený Milan: On stochastic conditional independence structures, European Conference on Higly Structured Stochastic Systems. Proceedings, p. 165-169, University of Aalborg (Rebild, 1996) [1996]
  53. Studený Milan: On Recovery Algorithm for Chain Graphs, ÚTIA AV ČR (Praha, 1996) [1996]
  54. Zvárová Jana, Studený Milan: Information theoretical approach to constitution and reduction of medical data. Abstract, EuroMISE '95: Information, Health and Education, p. 88, Eds: Zvárová J., Malá I., EuroMISE Center (Prague, 1995) [1995]
  55. Studený Milan: Marginal problem in different calculi of AI, Advances in Intelligent Computing - IPMU '94, p. 348-359, Eds: Bouchon-Meunier B., Yager R. R., Zadeh L. A., Springer (Berlin, 1995) [1995]
  56. Bouckaert R. R., Studený Milan: Chain graphs: semantics and expressiveness, Symbolic and Quantitative Approaches to Reasoning and Uncertainty, p. 67-76, Eds: Froidevaux Ch., Kohlas J., Springer (Berlin, 1995) [1995]
  57. Bouckaert R. R., Studený Milan: Chain Graphs: Semantics and Expressiveness - Extended Version, ÚTIA AV ČR (Praha, 1995) [1995]
  58. Zvárová Jana, Hrach Karel, Malá I., Peleška J., Studený Milan, Štefek Martin, Švejda David, Tomečková M.: Managing Uncertainty in Medicine, EuroMISE (Prague, 1995) [1995]
  59. Zvárová Jana, Studený Milan: Information Theoretical Approach to Constitution and Reduction of Medical Data, EuroMISE 95: Information, Health and Education, p. 88, Eds: Zvárová J., Malá I. [1995]
  60. Studený Milan, Boček Pavel: CI-models arising among 4 random variables, Uncertainty Processing in Expert Systems. Proceedings, p. 268-282, VŠE (Praha, 1994) [1994]
  61. Studený Milan: Semigraphoids are two-antecedental approximations of stochastic conditional independence models, Uncertainty in Artificial Intelligence. Proceedings, p. 546-552, Eds: Mantaras R. L., Poole D., Morgan Kaufmann (San Francisco, 1994) [1994]
  62. Studený Milan: Marginal problem in different calculi of AI, Information Processing and Management of Uncertainty in Knowledge-Based Systems. Proceedings, p. 597-604, Cité Internationale Universitaire (Paris, 1994) [1994]
  63. Studený Milan: Formal Properties of Conditional Independence in Different Calculi of AI, Symbolic and Quantitative Approaches to Reasoning and Uncertainty, p. 341-348, Eds: Clarke M., Kruse R., Moral S., Springer (Berlin, 1993) [1993]
  64. Studený Milan, Matúš František, Vejnarová Jiřina: Decomposition of Large Systems and Independence Structures, Second European Congress on Systems Science, p. 891-898, Afcet (Paris, 1993) [1993]
  65. Studený Milan: Popis struktur podmíněné stochastické nezávislosti pomocí formulí součinového typu, Sborník prací letní školy JČMF ROBUST '92, p. 146-155, Eds: Antoch J., Dohnal G., JČMF (Praha, 1992) [1992]
  66. Studený Milan: Description of Conditional Independence Structures by Means of Imsets: A Connection with Product Formula Validity, International Conference on Information Processing and Management of Uncertainty. IPMU '92, p. 503-506, Universitat des les Illes Balears (Palma, 1992) [1992]
  67. Studený Milan: Multiinformation and Conditional Independence II, ÚTIA ČSAV (Praha, 1992) [1992]
  68. Studený Milan: Conditional Independence Relations Have No Finite Complete Characterization, Transactions of the Eleventh Prague Conference on Information Theory, Statistical Decision Functions, Random Processes, p. 377-396, Academia (Prague, 1992) [1992]
  69. Lachout Petr, Studený Milan, Šindelář Jan: On Set-Valued Measures, ÚTIA ČSAV (Praha, 1992) [1992]
  70. Studený Milan: Convex set Functions II, ÚTIA ČSAV (Praha, 1991) [1991]
  71. Studený Milan: Convex Set Functions I, ÚTIA ČSAV (Praha, 1991) [1991]
  72. Studený Milan: Convex Semigraphoids, Workshop on Uncertainty Processing in Expert Systems, p. -, ÚTIA ČSAV (Prague, 1991) [1991]
  73. Studený Milan: Convex cones in Rn, ÚTIA ČSAV (Praha, 1991) [1991]
  74. Studený Milan: Multiinformace jakožto nástroj pro studium podmíněné stochastické nezávislosti, PROBASTAT '89. Zborník príspevkov, p. 129, VVTŠ (Liptovský Mikuláš, 1989) [1989]
  75. Studený Milan: Multiinformation and Conditional Independence I, ÚTIA ČSAV (Praha, 1989) [1989]
Created by SUITU websites SE, powered by SUITU CMS, © 2025
Intranet