Milan Studený

1.5k total citations
52 papers, 690 citations indexed

About

Milan Studený is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Milan Studený has authored 52 papers receiving a total of 690 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 20 papers in Computational Theory and Mathematics and 9 papers in Management Science and Operations Research. Recurrent topics in Milan Studený's work include Bayesian Modeling and Causal Inference (33 papers), Rough Sets and Fuzzy Logic (11 papers) and Multi-Criteria Decision Making (9 papers). Milan Studený is often cited by papers focused on Bayesian Modeling and Causal Inference (33 papers), Rough Sets and Fuzzy Logic (11 papers) and Multi-Criteria Decision Making (9 papers). Milan Studený collaborates with scholars based in Czechia, United Kingdom and United States. Milan Studený's co-authors include Remco Bouckaert, Francesco M. Malvestuto, Raymond Hemmecke, Jiří Vomlel, David Haws, František Matúš, Ian H. Witten, Jon Kleinberg, Alberto Roverato and Michael I. Jordan and has published in prestigious journals such as The Annals of Statistics, Information Sciences and Journal of Machine Learning Research.

In The Last Decade

Milan Studený

45 papers receiving 594 citations

Peers

Milan Studený
Adam R. Klivans United States
Desh Ranjan United States
Francesco M. Malvestuto Italy
Krzysztof Onak United States
Lane A. Hemachandra United States
T.J. Tjalkens Netherlands
Christine Rüb Germany
Richard C. T. Lee United States
Anup Rao United States
V. К. Trofimov Russia
Adam R. Klivans United States
Milan Studený
Citations per year, relative to Milan Studený Milan Studený (= 1×) peers Adam R. Klivans

Countries citing papers authored by Milan Studený

Since Specialization
Citations

This map shows the geographic impact of Milan Studený's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Milan Studený with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Milan Studený more than expected).

Fields of papers citing papers by Milan Studený

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Milan Studený. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Milan Studený. The network helps show where Milan Studený may publish in the future.

Co-authorship network of co-authors of Milan Studený

This figure shows the co-authorship network connecting the top 25 collaborators of Milan Studený. A scholar is included among the top collaborators of Milan Studený based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Milan Studený. Milan Studený is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Studený, Milan, et al.. (2021). The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture. International Journal of Approximate Reasoning. 138. 188–203.
2.
Studený, Milan, et al.. (2020). Dual Formulation of the Chordal Graph Conjecture. Explore Bristol Research. 449–460. 1 indexed citations
3.
Studený, Milan, et al.. (2018). Linear criterion for testing the extremity of an exact game based on its finest min-representation. International Journal of Approximate Reasoning. 101. 49–68.
4.
Studený, Milan & James Cussens. (2017). Towards using the chordal graph polytope in learning decomposable models. International Journal of Approximate Reasoning. 88. 259–281. 3 indexed citations
5.
Studený, Milan, et al.. (2017). Linear Core-Based Criterion for Testing Extreme Exact Games.. ASEP. 313–324. 1 indexed citations
6.
Studený, Milan & Tomáš Kroupa. (2016). Core-based criterion for extreme supermodular functions. Discrete Applied Mathematics. 206. 122–151. 7 indexed citations
7.
Studený, Milan. (2015). How matroids occur in the context of learning Bayesian network structure. ASEP. 832–841. 1 indexed citations
8.
Hemmecke, Raymond, et al.. (2012). Characteristic imsets for learning Bayesian network structure. International Journal of Approximate Reasoning. 53(9). 1336–1349. 26 indexed citations
9.
Bouckaert, Remco, et al.. (2010). Efficient Algorithms for Conditional Independence Inference. Journal of Machine Learning Research. 11(112). 3453–3479. 11 indexed citations
10.
Studený, Milan, et al.. (2009). TWO OPERATIONS OF MERGING AND SPLITTING COMPONENTS IN A CHAIN GRAPH. Kybernetika. 45(2). 208–248. 10 indexed citations
11.
Studený, Milan & Jiří Vomlel. (2008). A reconstruction algorithm for the essential graph. International Journal of Approximate Reasoning. 50(2). 385–413. 9 indexed citations
12.
Studený, Milan, et al.. (2007). Comparison of two methods for approximation of probability distributions with prescribed marginals. Kybernetika. 43(5). 591–618. 1 indexed citations
13.
Roverato, Alberto & Milan Studený. (2006). A Graphical Representation of Equivalence Classes of AMP Chain Graphs. Journal of Machine Learning Research. 7(38). 1045–1078. 15 indexed citations
14.
Studený, Milan. (2004). Probabilistic Conditional Independence Structures: With 42 Illustrations (Information Science and Statistics). Springer eBooks. 28 indexed citations
15.
Studený, Milan. (2002). Characterization of Essential Graphs by Means of an Operation of Legal Component Merging.. 4 indexed citations
16.
Dawid, A. P. & Milan Studený. (1999). Conditional products: An alternative approach to conditional independence. UCL Discovery (University College London). 7 indexed citations
17.
Studený, Milan. (1997). A recovery algorithm for chain graphs. International Journal of Approximate Reasoning. 17(2-3). 265–293. 30 indexed citations
18.
Studený, Milan. (1993). Convex cones in finite-dimensional real vector spaces. Kybernetika. 29(2). 180–200. 6 indexed citations
19.
Studený, Milan. (1989). Attempts at axiomatic description of conditional independence. Kybernetika. 25(4). 72–79. 14 indexed citations
20.
Studený, Milan. (1987). Asymptotic behaviour of empirical multiinformation. Kybernetika. 23(2). 124–135. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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