138 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Charles UniversityCZ11 papers
- Czech Academy of Sciences, Institute of Information Theory and AutomationCZ5 papers
- Czech Technical University in PragueCZ5 papers
- University of MannheimDE3 papers
- Johannes Kepler University of LinzAT2 papers
- Queen Mary University of LondonGB2 papers
- University of California, BerkeleyUS2 papers
- University of OxfordGB2 papers
- University of TurinIT2 papers
- Utrecht UniversityNL2 papers
- American UniversityUS1 paper
- Cambridge Econometrics (United Kingdom)GB1 paper
6 papers · 1 filter
Computing Enclosures of Overdetermined Interval Linear Systems
Jaroslav Horáček, Milan Hladík
This work considers special types of interval linear systems - overdetermined systems. Simply said these systems have more equations than variables. The solution set of an interval…
Composition of Probability Measures on Finite Spaces
Radim Jirousek
Decomposable models and Bayesian networks can be defined as sequences of oligo-dimensional probability measures connected with operators of composition. The preliminary results sug…
Conditional Independence and Markov Properties in Possibility Theory
Jirina Vejnarova
Conditional independence and Markov properties are powerful tools allowing expression of multidimensional probability distributions by means of low-dimensional ones. As multidimens…
Marginalization in Composed Probabilistic Models
Radim Jirousek
Composition of low-dimensional distributions, whose foundations were laid in the papaer published in the Proceeding of UAI'97 (Jirousek 1997), appeared to be an alternative apparat…
Improved learning of Bayesian networks
Tomas Kocka, Robert Castelo
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Bayes…
On characterizing Inclusion of Bayesian Networks
Tomas Kocka, Remco R. Bouckaert, Milan Studeny
Every directed acyclic graph (DAG) over a finite non-empty set of variables (= nodes) N induces an independence model over N, which is a list of conditional independence statements…