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Boris G. Mirkin
Boris Grigor'evich Mirkin
Person information
- affiliation: National Research University Higher School of Economics, Moscow, Department of Data Analysis and Machine Intelligence
- affiliation: Birkbeck University of London, Department of Computer Science and Information Systems
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2020 – today
- 2024
- [j40]Andrei Rykov
, Renato Cordeiro de Amorim
Inertia-Based Indices to Determine the Number of Clusters in K-Means: An Experimental Evaluation. IEEE Access 12: 11761-11773 (2024) - 2023
- [j39]Susana Nascimento
Piece-wise constant cluster modelling of dynamics of upwelling patterns. Expert Syst. J. Knowl. Eng. 40(10) (2023) - [j38]Susana Nascimento
Core-shell clustering approach for detection and analysis of coastal upwelling. Comput. Geosci. 179: 105421 (2023) - [c52]Soroosh Shalileh, Boris G. Mirkin:
Community Detection in Feature-Rich Networks Using Gradient Descent Approach. COMPLEX NETWORKS (2) 2023: 185-196 - 2022
- [j37]Boris G. Mirkin
Community Detection in Feature-Rich Networks Using Data Recovery Approach. J. Classif. 39(3): 432-462 (2022) - [j36]Soroosh Shalileh
Community Partitioning over Feature-Rich Networks Using an Extended K-Means Method. Entropy 24(5): 626 (2022) - [c51]Susana Nascimento
Novel Cluster Modeling for the Spatiotemporal Analysis of Coastal Upwelling. EPIA 2022: 563-574 - [c50]Zhirayr Hayrapetyan, Susana Nascimento
Modeling Generalization in Domain Taxonomies Using a Maximum Likelihood Criterion. WorldCIST (2) 2022: 141-147 - 2021
- [j35]Soroosh Shalileh
Summable and nonsummable data-driven models for community detection in feature-rich networks. Soc. Netw. Anal. Min. 11(1): 67 (2021) - [c49]Soroosh Shalileh
Community detection in feature-rich networks to meet K-means. ASONAM 2021: 138-142 - [c48]Soroosh Shalileh
An Extension of K-Means for Least-Squares Community Detection in Feature-Rich Networks. COMPLEX NETWORKS 2021: 285-296 - [c47]Soroosh Shalileh
Detecting Communities in Feature-Rich Networks with a K-Means Method. IDEAL 2021: 539-547 - [c46]Dmitry Frolov, Boris G. Mirkin
GOT: Generalization over Taxonomies, a Software Toolkit for Content Analysis with Taxonomies. WorldCIST (2) 2021: 513-521 - 2020
- [j34]Renato Cordeiro de Amorim
Core Clustering as a Tool for Tackling Noise in Cluster Labels. J. Classif. 37(1): 143-157 (2020) - [j33]Dmitry Frolov
Parsimonious generalization of fuzzy thematic sets in taxonomies applied to the analysis of tendencies of research in data science. Inf. Sci. 512: 595-615 (2020) - [c45]Soroosh Shalileh
A Data Recovery Method for Community Detection in Feature-Rich Networks. ASONAM 2020: 99-104 - [c44]Soroosh Shalileh
A Method for Community Detection in Networks with Mixed Scale Features at Its Nodes. COMPLEX NETWORKS (1) 2020: 3-14 - [c43]Soroosh Shalileh
A One-by-One Method for Community Detection in Attributed Networks. IDEAL (2) 2020: 413-422 - [c42]Boris G. Mirkin
A Hybrid Approach to the Analysis of a Collection of Research Papers. IDEAL (2) 2020: 423-433 - [c41]Soroosh Shalileh, Boris G. Mirkin:
Detection of an Unspecified Number of Communities in Feature-Rich Networks. MARAMI 2020 - [c40]Boris G. Mirkin
A Hybrid Approach to Interpretable Analysis of Research Paper Collections. WIMS 2020: 184-189
2010 – 2019
- 2019
- [b3]Boris G. Mirkin:
Core Data Analysis: Summarization, Correlation, and Visualization, Second Edition. Undergraduate Topics in Computer Science, Springer 2019, ISBN 978-3-030-00270-1, pp. 1-475 - [j32]Boris G. Mirkin
Distance and Consensus for Preference Relations Corresponding to Ordered Partitions. J. Classif. 36(2): 350-367 (2019) - [c39]Zina Taran
Deriving Corporate Social Responsibility Patterns in the MSCI Data. BIS (1) 2019: 112-121 - [c38]Dmitry Frolov, Susana Nascimento
Using Taxonomy Tree to Generalize a Fuzzy Thematic Cluster. FUZZ-IEEE 2019: 1-6 - [c37]Dmitry Frolov
Method for Generalization of Fuzzy Sets. ICAISC (1) 2019: 273-286 - [c36]Dmitry Frolov, Susana Nascimento
Computational Generalization in Taxonomies Applied to: (1) Analyze Tendencies of Research and (2) Extend User Audiences. IDEAL (2) 2019: 3-11 - [c35]Alexey L. Myachin
Ordinal Equivalence Classes for Parallel Coordinates. IDEAL (1) 2019: 525-533 - [c34]Dmitry Frolov, Zina Taran, Boris G. Mirkin
A Method for Audience Extending in Programmatic Advertising by Using Parsimonious Generalization of User Segments. IHIET 2019: 837-841 - [c33]Dmitry Frolov, Boris G. Mirkin
Globally Optimal Parsimoniously Lifting a Fuzzy Query Set Over a Taxonomy Tree. WCGO 2019: 779-789 - 2018
- [j31]Fionn Murtagh, Michael Orlov, Boris G. Mirkin
Qualitative Judgement of Research Impact: Domain Taxonomy as a Fundamental Framework for Judgement of the Quality of Research. J. Classif. 35(1): 5-28 (2018) - [e4]Lev I. Rozonoer, Boris G. Mirkin, Ilya Muchnik:
Braverman Readings in Machine Learning. Key Ideas from Inception to Current State - International Conference Commemorating the 40th Anniversary of Emmanuil Braverman's Decease, Boston, MA, USA, April 28-30, 2017, Invited Talks. Lecture Notes in Computer Science 11100, Springer 2018, ISBN 978-3-319-99491-8 [contents] - 2017
- [j30]Renato Cordeiro de Amorim
The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning. Pattern Recognit. 67: 62-72 (2017) - [c32]Boris G. Mirkin
Braverman's Spectrum and Matrix Diagonalization Versus iK-Means: A Unified Framework for Clustering. Braverman Readings in Machine Learning 2017: 32-51 - [c31]Boris G. Mirkin
Misha Braverman: My Mentor and My Model. Braverman Readings in Machine Learning 2017: 341-348 - [c30]Susana Nascimento
Ideal type model and an associated method for relational fuzzy clustering. FUZZ-IEEE 2017: 1-6 - [c29]Ivan Rodin, Boris G. Mirkin
Supercluster in Statics and Dynamics: An Approximate Structure Imitating a Rough Set. IJCRS (1) 2017: 576-586 - 2016
- [j29]Renato Cordeiro de Amorim
A-Wardpβ: Effective hierarchical clustering using the Minkowski metric and a fast k-means initialisation. Inf. Sci. 370-371: 343-354 (2016) - [c28]Artem Bocharov, Dmitry Gnatyshak, Dmitry I. Ignatov, Boris G. Mirkin, Andrey Shestakov:
A Lattice-based Consensus Clustering Algorithm. CLA 2016: 45-56 - [c27]Ivan Rodin, Ekaterina Chernyak, Mikhail Dubov, Boris G. Mirkin
Visualization of Dynamic Reference Graphs. TextGraphs@NAACL-HLT 2016: 34-38 - [i3]Fionn Murtagh, Michael Orlov, Boris G. Mirkin:
Qualitative Judgement of Research Impact: Domain Taxonomy as a Fundamental Framework for Judgement of the Quality of Research. CoRR abs/1607.03200 (2016) - [i2]Renato Cordeiro de Amorim, Vladimir Makarenkov, Boris G. Mirkin:
A-Wardpβ: Effective hierarchical clustering using the Minkowski metric and a fast k -means initialisation. CoRR abs/1611.01060 (2016) - 2015
- [j28]Ekaterina V. Kovaleva, Boris G. Mirkin
Bisecting K-Means and 1D Projection Divisive Clustering: A Unified Framework and Experimental Comparison. J. Classif. 32(3): 414-442 (2015) - [j27]Susana Nascimento
A seed expanding cluster algorithm for deriving upwelling areas on sea surface temperature images. Comput. Geosci. 85: 74-85 (2015) - [j26]Dmitry I. Ignatov
Triadic Formal Concept Analysis and triclustering: searching for optimal patterns. Mach. Learn. 101(1-3): 271-302 (2015) - [j25]Boris G. Mirkin:
Book review "Cell formation in industrial engineering: theory, algorithms and experiments" by Boris Goldengorin, Dmitry Krushinsky, Panos M. Pardalos - Springer, 2013. Optim. Lett. 9(6): 1259-1262 (2015) - 2014
- [c26]Egor N. Morenko, Ekaterina Chernyak, Boris G. Mirkin
Conceptual Maps: Construction Over a Text Collection and Analysis. AIST 2014: 163-168 - [c25]Ekaterina Chernyak, Boris G. Mirkin
A Method for Refining a Taxonomy by Using Annotated Suffix Trees and Wikipedia Resources. ITQM 2014: 193-200 - [c24]Mikhail Orlov, Boris G. Mirkin
A Concept of Multicriteria Stratification: A Definition and Solution. ITQM 2014: 273-280 - 2013
- [j24]Susana Nascimento
Laplacian normalization for deriving thematic fuzzy clusters with an additive spectral approach. Expert Syst. J. Knowl. Eng. 30(4): 294-305 (2013) - [c23]Boris G. Mirkin
Least Square Consensus Clustering: Criteria, Methods, Experiments. ECIR 2013: 764-767 - [c22]L. Svetlova, Boris G. Mirkin
MFWK-Means: Minkowski metric Fuzzy Weighted K-Means for high dimensional data clustering. IRI 2013: 692-699 - [c21]Renato Cordeiro de Amorim, Boris G. Mirkin
A Clustering-Based Approach to Reduce Feature Redundancy. KICSS 2013: 465-475 - [c20]Boris G. Mirkin
Individual Approximate Clusters: Methods, Properties, Applications. RSFDGrC 2013: 26-37 - [p2]Boris G. Mirkin
Methods for Interpretation of Data in Medical Informatics. Advances in Intelligent Analysis of Medical Data and Decision Support Systems 2013: 15-22 - 2012
- [j23]Renato Cordeiro de Amorim, Boris G. Mirkin, John Q. Gan:
Anomalous pattern based clustering of mental tasks with subject independent learning - some preliminary results. Artif. Intell. Res. 1(1): 55-62 (2012) - [j22]Boris G. Mirkin
Additive spectral method for fuzzy cluster analysis of similarity data including community structure and affinity matrices. Inf. Sci. 183(1): 16-34 (2012) - [j21]Renato Cordeiro de Amorim
Minkowski metric, feature weighting and anomalous cluster initializing in K-Means clustering. Pattern Recognit. 45(3): 1061-1075 (2012) - 2011
- [b2]Boris G. Mirkin:
Core Concepts in Data Analysis: Summarization, Correlation and Visualization. Undergraduate Topics in Computer Science, Springer 2011, ISBN 978-0-85729-286-5, pp. i-xx, 1-390 - [j20]Boris G. Mirkin
Choosing the number of clusters. WIREs Data Mining Knowl. Discov. 1(3): 252-260 (2011) - [c19]Susana Nascimento
Thematic Fuzzy Clusters with an Additive Spectral Approach. EPIA 2011: 446-461 - [c18]Boris G. Mirkin
How to Visualize a Crisp or Fuzzy Topic Set over a Taxonomy. PReMI 2011: 3-12 - [c17]Boris G. Mirkin
Approximate Bicluster and Tricluster Boxes in the Analysis of Binary Data. RSFDGrC 2011: 248-256 - [c16]Boris G. Mirkin
Developing Additive Spectral Approach to Fuzzy Clustering. RSFDGrC 2011: 273-277 - [e3]Sergei O. Kuznetsov
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing - 13th International Conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011. Proceedings. Lecture Notes in Computer Science 6743, Springer 2011, ISBN 978-3-642-21880-4 [contents] - 2010
- [j19]Mark Ming-Tso Chiang, Boris G. Mirkin
Intelligent Choice of the Number of Clusters in K-Means Clustering: An Experimental Study with Different Cluster Spreads. J. Classif. 27(1): 3-40 (2010) - [j18]Zacharias Voulgaris, Boris G. Mirkin
Choosing a discernibility measure for reject-option of individual and multiple classifiers. Int. J. Gen. Syst. 39(8): 855-871 (2010) - [j17]Boris G. Mirkin, Susana Nascimento, Trevor I. Fenner, Luís Moniz Pereira:
Building Fuzzy Thematic Clusters and Mapping Them to Higher Ranks in a Taxonomy. Int. J. Softw. Informatics 4(3): 257-275 (2010) - [c15]Boris G. Mirkin
A Hybrid Cluster-Lift Method for the Analysis of Research Activities. HAIS (1) 2010: 152-161 - [c14]Boris G. Mirkin
Constructing and Mapping Fuzzy Thematic Clusters to Higher Ranks in a Taxonomy. KSEM 2010: 329-340 - [p1]Boris G. Mirkin
Cluster-Lift Method for Mapping Research Activities over a Concept Tree. Advances in Machine Learning II 2010: 245-257
2000 – 2009
- 2009
- [j16]Boris G. Mirkin
Special Issue on Profiling Expertise and Behaviour. Comput. J. 52(7): 727-728 (2009) - [c13]Valentina Sulimova, Vadim Mottl, Boris G. Mirkin
A Class of Evolution-Based Kernels for Protein Homology Analysis: A Generalization of the PAM Model. ISBRA 2009: 284-296 - 2008
- [j15]Dirk Depril, Iven Van Mechelen, Boris G. Mirkin
Algorithms for additive clustering of rectangular data tables. Comput. Stat. Data Anal. 52(11): 4923-4938 (2008) - [c12]Boris G. Mirkin, Susana Nascimento, Luís Moniz Pereira:
Representing a Computer Science Research Organization on the ACM Computing Classification System. ICCS Supplement 2008: 57-65 - 2007
- [c11]Boris G. Mirkin:
Approximate Clusters and Biclusters (Abstract). CLA 2007 - [c10]Mark Ming-Tso Chiang, Boris G. Mirkin
Experiments for the Number of Clusters in K-Means. EPIA Workshops 2007: 395-405 - 2006
- [j14]Ito Wasito
Nearest neighbours in least-squares data imputation algorithms with different missing patterns. Comput. Stat. Data Anal. 50(4): 926-949 (2006) - [j13]Rajesh Mysore Pampapathi, Boris G. Mirkin
A suffix tree approach to anti-spam email filtering. Mach. Learn. 65(1): 309-338 (2006) - [c9]Boris G. Mirkin
Aggregating Homologous Protein Families in Evolutionary Reconstructions of Herpesviruses. CIBCB 2006: 1-8 - 2005
- [b1]Boris G. Mirkin:
Clustering for data mining - a data recovery approach. Computer science and data analysis series, Chapman & Hall 2005, ISBN 978-1-58488-534-4, pp. I-XXIII, 1-266 - [j12]Ito Wasito
Nearest neighbour approach in the least-squares data imputation algorithms. Inf. Sci. 169(1-2): 1-25 (2005) - [i1]Rajesh Mysore Pampapathi, Boris G. Mirkin, Mark Levene:
A Suffix Tree Approach to Email Filtering. CoRR abs/cs/0503030 (2005) - 2003
- [j11]Boris G. Mirkin:
Comments on "Exact output tracking in decentralized adaptive control". IEEE Trans. Autom. Control. 48(2): 348-350 (2003) - [j10]Susana Nascimento
Modeling proportional membership in fuzzy clustering. IEEE Trans. Fuzzy Syst. 11(2): 173-186 (2003) - [e2]Melvin F. Janowitz, François-Joseph Lapointe, Fred R. McMorris, Boris G. Mirkin, Fred S. Roberts:
Bioconsensus, Proceedings of a DIMACS Workshop, New Brunswick, New Jersey, USA, 2001. DIMACS Series in Discrete Mathematics and Theoretical Computer Science 61, DIMACS/AMS 2003, ISBN 978-0-8218-3197-7 [contents] - 2002
- [j9]Boris G. Mirkin
Layered clusters of tightness set functions. Appl. Math. Lett. 15(2): 147-151 (2002) - [j8]Boris G. Mirkin
Induced layered clusters, hereditary mappings, and convex geometries. Appl. Math. Lett. 15(3): 293-298 (2002) - 2001
- [j7]Boris G. Mirkin
Reinterpreting the Category Utility Function. Mach. Learn. 45(2): 219-228 (2001) - [c8]Boris G. Mirkin, Eugene V. Koonin:
A top-down method for building genome classification trees with linear binary hierarchies. Bioconsensus 2001: 97-111 - [c7]Susana Nascimento
Proportional Membership in Fuzzy Clustering as a Model of Ideal Types. EPIA 2001: 52-62 - 2000
- [c6]Susana Nascimento, Boris G. Mirkin, Fernando Moura-Pires:
A fuzzy clustering model of data and fuzzy c-means. FUZZ-IEEE 2000: 302-307
1990 – 1999
- 1999
- [j6]Boris G. Mirkin
Concept Learning and Feature Selection Based on Square-Error Clustering. Mach. Learn. 35(1): 25-39 (1999) - [c5]Susana Nascimento
Multiple Prototype Model for Fuzzy Clustering. IDA 1999: 269-280 - 1998
- [j5]Boris G. Mirkin
Least-Squares Structuring, Clustering and Data Processing Issues. Comput. J. 41(8): 518-536 (1998) - [j4]Oliver Eulenstein, Boris G. Mirkin
Duplication-Based Measures of Difference Between Gene and Species Trees. J. Comput. Biol. 5(1): 135-148 (1998) - 1997
- [e1]Boris G. Mirkin, Fred R. McMorris, Fred S. Roberts, Andrey Rzhetsky:
Mathematical Hierarchies and Biology, Proceedings of a DIMACS Workshop, November 13-15, 1996. DIMACS Series in Discrete Mathematics and Theoretical Computer Science 37, DIMACS/AMS 1997, ISBN 978-0-8218-0762-0 [contents] - 1996
- [j3]Boris G. Mirkin
Clustering for contingency tables: boxes and partitions. Stat. Comput. 6(3): 217-229 (1996) - [c4]Oliver Eulenstein, Boris G. Mirkin, Martin Vingron:
Comparison of annotating duplication, tree mapping, and copying as methods to compare gene trees with species trees. Mathematical Hierarchies and Biology 1996: 71-94 - [c3]Boris G. Mirkin:
Linear embedding of binary hierarchies and its applications. Mathematical Hierarchies and Biology 1996: 331-356 - 1995
- [j2]Boris G. Mirkin
A Biologically Consistent Model for Comparing Molecular Phylogenies. J. Comput. Biol. 2(4): 493-507 (1995) - 1993
- [c2]Boris G. Mirkin:
Approximation of Association Data by Structures and Clusters. Quadratic Assignment and Related Problems 1993: 293-316
1980 – 1989
- 1982
- [j1]Boris G. Mirkin
Federations and transitive group choice. Math. Soc. Sci. 2(1): 35-38 (1982)
1970 – 1979
- 1974
- [c1]Boris G. Mirkin
Group Choice and Extremal Problems in the Analysis of Qualitative Attributes. Optimization Techniques 1974: 56-61
Coauthor Index
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