Milan Studený

Discret. Appl. Math., 2025

2022

Algorithmic Aspects of Information Theory (Dagstuhl Seminar 22301).

[BibT_eX]

[DOI]

Phokion G. Kolaitis

Andrej E. Romashchenko

Dan Suciu

Tobias Boege

Dagstuhl Reports, July, 2022

Facets of the cone of exact games.

[BibT_eX]

[DOI]

Math. Methods Oper. Res., 2022

2021

Conditional Independence Structures Over Four Discrete Random Variables Revisited: Conditional Ingleton Inequalities.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2021

The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2021

2020

Contribution of Frantisek Matus to the research on conditional independence.

[BibT_eX]

[DOI]

Kybernetika, 2020

Special issue in memory of František Matúš.

[BibT_eX]

[DOI]

Nihat Ay

Kybernetika, 2020

Dual Formulation of the Chordal Graph Conjecture.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

2019

Facets of the cone of totally balanced games.

[BibT_eX]

[DOI]

Tomás Kroupa

Math. Methods Oper. Res., 2019

On Irreducible Min-Balanced Set Systems.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2019

2018

Linear criterion for testing the extremity of an exact game based on its finest min-representation.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2018

Proceedings of the 9th International Conference on Probabilistic Graphical Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017

Polyhedral aspects of score equivalence in Bayesian network structure learning.

[BibT_eX]

[DOI]

David Haws

Math. Program., 2017

Towards using the chordal graph polytope in learning decomposable models.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2017

Linear Core-Based Criterion for Testing Extreme Exact Games.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, 2017

2016

Core-based criterion for extreme supermodular functions.

[BibT_eX]

[DOI]

Tomás Kroupa

Discret. Appl. Math., 2016

The Chordal Graph Polytope for Learning Decomposable Models.

[BibT_eX]

[DOI]

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

2015

How matroids occur in the context of learning Bayesian network structure.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

2014

Learning Bayesian network structure: Towards the essential graph by integer linear programming tools.

[BibT_eX]

[DOI]

David Haws

Int. J. Approx. Reason., 2014

2012

Characteristic imsets for learning Bayesian network structure.

[BibT_eX]

[DOI]

Raymond Hemmecke

Silvia Lindner

Int. J. Approx. Reason., 2012

2011

On open questions in the geometric approach to structural learning Bayesian nets.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2011

2010

Efficient Algorithms for Conditional Independence Inference.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2010

A geometric view on learning Bayesian network structures.

[BibT_eX]

[DOI]

Raymond Hemmecke

Int. J. Approx. Reason., 2010

Learning restricted Bayesian network structures

[BibT_eX]

[DOI]

Raymond Hemmecke

Silvia Lindner

CoRR, 2010

2009

Two Operations of Merging and Splitting Components in a Chain Graph.

[BibT_eX]

[DOI]

Alberto Roverato

Sárka Stepánová

Kybernetika, 2009

A reconstruction algorithm for the essential graph.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2009

2008

Editorial Note.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2008

2007

Comparison of two methods for approximation of probability distributions with prescribed marginals.

[BibT_eX]

[DOI]

Albert Perez

Kybernetika, 2007

Racing algorithms for conditional independence inference.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2007

2006

A Graphical Representation of Equivalence Classes of AMP Chain Graphs.

[BibT_eX]

[DOI]

Alberto Roverato

J. Mach. Learn. Res., 2006

2005

Characterization of inclusion neighbourhood in terms of the essential graph.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2005

Racing for Conditional Independence Inference.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2005

Probabilistic conditional independence structures.

[BibT_eX]

Information science and statistics, Springer, ISBN: 978-1-85233-891-6, 2005

2004

Characterization Of Essential Graphs By Means Of The Operation Of Legal Merging Of Components.

[BibT_eX]

[DOI]

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2004

2003

Characterization of Inclusion Neighbourhood in Terms of the Essential Graph: Uper Neighbours.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2003

2002

On Stochastic Conditional Independence: the Problems of Characterization and Description.

[BibT_eX]

[DOI]

Ann. Math. Artif. Intell., 2002

Characterization of Essential Graphs by Means of an Operation of Legal Component Merging.

[BibT_eX]

[DOI]

Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

2001

On characterizing Inclusion of Bayesian Networks.

[BibT_eX]

[DOI]

Tomás Kocka

Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

2000

Representation of Irrelevance Relations by Annotated Graphs.

[BibT_eX]

[DOI]

Azaria Paz

Robert Y. Geva

Fundam. Informaticae, 2000

1999

A graphical characterization of the largest chain graphs.

[BibT_eX]

[DOI]

Martin Volf

Int. J. Approx. Reason., 1999

Conditional products: An alternative approach to conditional independence.

[BibT_eX]

[DOI]

A. Philip Dawid

Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

1998

Bayesian Networks from the Point of View of Chain Graphs.

[BibT_eX]

[DOI]

Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

The Multiinformation Function as a Tool for Measuring Stochastic Dependence.

[BibT_eX]

[DOI]

Jirina Vejnarová

Proceedings of the Learning in Graphical Models, 1998

1997

A recovery algorithm for chain graphs.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 1997

Semigraphoids and Structures of Probabilistic Conditional Independence.

[BibT_eX]

[DOI]

Ann. Math. Artif. Intell., 1997

1996

On Separation Criterion and Recovery Algorithm for Chain Graphs.

[BibT_eX]

[DOI]

Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

1995

Conditional independence and natural conditional functions.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 1995

Conditional Independences among Four Random Variables 1.

[BibT_eX]

[DOI]

Frantisek Matús

Comb. Probab. Comput., 1995

Chain graphs: semantics and expressiveness.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1995

1994

Semigraphoids Are Two-Antecedental Approximations of Stochastic Conditional Independence Models.

[BibT_eX]

[DOI]

Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

Marginal Problem in Different Calculi of AI.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Computing, 1994

1993

Convex cones in finite-dimensional real vector spaces.

[BibT_eX]

[DOI]

Kybernetika, 1993

Formal Properties of Conditional Independence in Different Calculi of AI.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1993

1992

Comment on "A unique formal system for binary decompositions of database relations, probability distributions, and graphs".

[BibT_eX]

[DOI]

Francesco M. Malvestuto

Inf. Sci., 1992

1989

Attempts at axiomatic description of conditional independence.

[BibT_eX]

[DOI]

Kybernetika, 1989

1987

Asymptotic behaviour of empirical multiinformation.

[BibT_eX]

[DOI]