Milan Studený

Publication Activity (10 Years)

Years Active: 1987-2024
Publications (10 Years): 20

Top Topics

Graphical Models

Conditional Independence

Random Variables

Bayesian Network Structure

Top Venues

Int. J. Approx. Reason.

Math. Methods Oper. Res.

Publications

Tobias A. Boege, Janneke H. Bolt, Milan Studený
Self-adhesivity in lattices of abstract conditional independence models. CoRR (2024)
Milan Studený, Václav Kratochvíl
Facets of the cone of exact games. Math. Methods Oper. Res. 95 (1) (2022)
Phokion G. Kolaitis, Andrej E. Romashchenko, Milan Studený, Dan Suciu, Tobias A. Boege
Algorithmic Aspects of Information Theory (Dagstuhl Seminar 22301). Dagstuhl Reports 12 (7) (2022)
Milan Studený
Conditional Independence Structures Over Four Discrete Random Variables Revisited: Conditional Ingleton Inequalities. IEEE Trans. Inf. Theory 67 (11) (2021)
Milan Studený, James Cussens, Václav Kratochvíl
The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture. Int. J. Approx. Reason. 138 (2021)
Milan Studený, Václav Kratochvíl
Facets of the cone of exact games. CoRR (2021)
Milan Studený
Contribution of Frantisek Matus to the research on conditional independence. Kybernetika 56 (5) (2020)
Nihat Ay, Milan Studený
Special issue in memory of František Matúš. Kybernetika 56 (6) (2020)
Milan Studený
Conditional independence structures over four discrete random variables revisited: conditional Ingleton inequalities. CoRR (2020)
Milan Studený, James Cussens, Václav Kratochvíl
Dual Formulation of the Chordal Graph Conjecture. PGM (2020)
Tomás Kroupa, Milan Studený
Facets of the cone of totally balanced games. Math. Methods Oper. Res. 90 (2) (2019)
Milan Studený, Václav Kratochvíl, Jirí Vomlel
On Irreducible Min-Balanced Set Systems. ECSQARU (2019)
Václav Kratochvíl, Milan Studený
Proceedings of the 9th International Conference on Probabilistic Graphical Models. PGM (2018)
Milan Studený, Václav Kratochvíl
Linear criterion for testing the extremity of an exact game based on its finest min-representation. Int. J. Approx. Reason. 101 (2018)
Milan Studený, James Cussens
Towards using the chordal graph polytope in learning decomposable models. Int. J. Approx. Reason. 88 (2017)
Milan Studený, Václav Kratochvíl
Linear Core-Based Criterion for Testing Extreme Exact Games. ISIPTA (2017)
James Cussens, David Haws, Milan Studený
Polyhedral aspects of score equivalence in Bayesian network structure learning. Math. Program. 164 (1-2) (2017)
Milan Studený, Tomás Kroupa
Core-based criterion for extreme supermodular functions. Discret. Appl. Math. 206 (2016)
Milan Studený, James Cussens
The Chordal Graph Polytope for Learning Decomposable Models. Probabilistic Graphical Models (2016)
Milan Studený
How matroids occur in the context of learning Bayesian network structure. UAI (2015)
Milan Studený, David Haws
Learning Bayesian network structure: Towards the essential graph by integer linear programming tools. Int. J. Approx. Reason. 55 (4) (2014)
Tomas Kocka, Remco R. Bouckaert, Milan Studený
On characterizing Inclusion of Bayesian Networks CoRR (2013)
Milan Studený
Semigraphoids Are Two-Antecedental Approximations of Stochastic Conditional Independence Models CoRR (2013)
Milan Studený
On Separation Criterion and Recovery Algorithm for Chain Graphs CoRR (2013)
Milan Studený
Bayesian Networks from the Point of View of Chain Graphs CoRR (2013)
Raymond Hemmecke, Silvia Lindner, Milan Studený
Characteristic imsets for learning Bayesian network structure. Int. J. Approx. Reason. 53 (9) (2012)
Milan Studený, Jirí Vomlel
On open questions in the geometric approach to structural learning Bayesian nets. Int. J. Approx. Reason. 52 (5) (2011)
Raymond Hemmecke, Silvia Lindner, Milan Studený
Learning restricted Bayesian network structures CoRR (2010)
Milan Studený, Jirí Vomlel, Raymond Hemmecke
A geometric view on learning Bayesian network structures. Int. J. Approx. Reason. 51 (5) (2010)
Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindner, Milan Studený
Efficient Algorithms for Conditional Independence Inference. J. Mach. Learn. Res. 11 (2010)
Milan Studený, Jirí Vomlel
A reconstruction algorithm for the essential graph. Int. J. Approx. Reason. 50 (2) (2009)
Milan Studený, Alberto Roverato, Sárka Stepánová
Two Operations of Merging and Splitting Components in a Chain Graph. Kybernetika 45 (2) (2009)
Milan Studený, Jirí Vomlel
Editorial Note. Int. J. Approx. Reason. 49 (2) (2008)
Albert Perez, Milan Studený
Comparison of two methods for approximation of probability distributions with prescribed marginals. Kybernetika 43 (5) (2007)
Remco R. Bouckaert, Milan Studený
Racing algorithms for conditional independence inference. Int. J. Approx. Reason. 45 (2) (2007)
Alberto Roverato, Milan Studený
A Graphical Representation of Equivalence Classes of AMP Chain Graphs. J. Mach. Learn. Res. 7 (2006)
Milan Studený
Characterization of inclusion neighbourhood in terms of the essential graph. Int. J. Approx. Reason. 38 (3) (2005)
Remco R. Bouckaert, Milan Studený
Racing for Conditional Independence Inference. ECSQARU (2005)
Milan Studený
Characterization Of Essential Graphs By Means Of The Operation Of Legal Merging Of Components. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 12 (Supplement-1) (2004)
Milan Studený
Characterization of Inclusion Neighbourhood in Terms of the Essential Graph: Uper Neighbours. ECSQARU (2003)
Milan Studený
On Stochastic Conditional Independence: the Problems of Characterization and Description. Ann. Math. Artif. Intell. 35 (1-4) (2002)
Milan Studený
Characterization of Essential Graphs by Means of an Operation of Legal Component Merging. Probabilistic Graphical Models (2002)
Tomás Kocka, Remco R. Bouckaert, Milan Studený
On characterizing Inclusion of Bayesian Networks. UAI (2001)
Azaria Paz, Robert Y. Geva, Milan Studený
Representation of Irrelevance Relations by Annotated Graphs. Fundam. Informaticae 42 (2) (2000)
A. Philip Dawid, Milan Studený
Conditional products: An alternative approach to conditional independence. AISTATS (1999)
Martin Volf, Milan Studený
A graphical characterization of the largest chain graphs. Int. J. Approx. Reason. 20 (3) (1999)
Milan Studený
Bayesian Networks from the Point of View of Chain Graphs. UAI (1998)
Milan Studený
Semigraphoids and Structures of Probabilistic Conditional Independence. Ann. Math. Artif. Intell. 21 (1) (1997)
Milan Studený
A recovery algorithm for chain graphs. Int. J. Approx. Reason. 17 (2-3) (1997)
Milan Studený
On Separation Criterion and Recovery Algorithm for Chain Graphs. UAI (1996)
Frantisek Matús, Milan Studený
Conditional Independences among Four Random Variables 1. Comb. Probab. Comput. 4 (1995)
Remco R. Bouckaert, Milan Studený
Chain graphs: semantics and expressiveness. ECSQARU (1995)
Milan Studený
Conditional independence and natural conditional functions. Int. J. Approx. Reason. 12 (1) (1995)
Milan Studený
Marginal Problem in Different Calculi of AI. IPMU (1994)
Milan Studený
Semigraphoids Are Two-Antecedental Approximations of Stochastic Conditional Independence Models. UAI (1994)
Milan Studený
Convex cones in finite-dimensional real vector spaces. Kybernetika 29 (2) (1993)
Milan Studený
Formal Properties of Conditional Independence in Different Calculi of AI. ECSQARU (1993)
Francesco M. Malvestuto, Milan Studený
Comment on "A unique formal system for binary decompositions of database relations, probability distributions, and graphs". Inf. Sci. 63 (1-2) (1992)
Milan Studený
Attempts at axiomatic description of conditional independence. Kybernetika 25 (7) (1989)
Milan Studený
Asymptotic behaviour of empirical multiinformation. Kybernetika 23 (2) (1987)