Участник:Vokov/Publications

Материал из MachineLearning.

Publications of Konstantin Vorontsov

Here only English publications are noted, most of my publications are in Russian.

1. Vorontsov K. Preliminary data processing for a special class of recognition problems // Comp. Maths Math. Phys. — 1995. — Vol. 35, no. 10. — Pp. 1259–1267. PDF, 400Kb.
2. Vorontsov K. The task-oriented optimization of bases in recognition problems // Comp. Maths Math. Phys. — 1998. — Vol. 38, no. 5. — Pp. 838–847. PDF, 580Kb.
3. Rudakov K., Vorontsov K. Methods of optimization and monotone correction in the algebraic approach to the recognition problem // Doklady Mathematics. — 1999. — Vol. 60, no. 1. — P. 139.
4. Vorontsov K. Optimization methods for linear and monotone correction in the algebraic approach to the recognition problem // Comp. Maths Math. Phys. — 2000. — Vol. 40, no. 1. — Pp. 159–168.
5. Vorontsov K. Combinatorial substantiation of learning algorithms // Comp. Maths Math. Phys. — 2004. — Vol. 44, no. 11. — Pp. 1997–2009. PDF, 206Kb.
6. Vorontsov K. Combinatorial bounds for learning performance // Doklady Mathematics. — 2004. — Vol. 69, no. 1. — Pp. 145––148. PDF, 44Kb.
7. Kanevskiy D., Vorontsov K. Cooperative coevolutionary ensemble learning // Multiple Classifier Systems: 7th International Workshop, Prague, Czech Republic, May 23-25, 2007. — Lecture Notes in Computer Science. Springer-Verlag, 2007. — Pp. 469–478. PDF, 155Kb.
8. Leksin V., Vorontsov K. The overfitting in probabilistic latent semantic models // Pattern Recognition and Image Analysis: new information technologies (PRIA-9-2008). — Vol. 1. — Nizhni Novgorod, Russian Federation, 2008. — Pp. 393–396. PDF, 250Kb.
9. Vorontsov K. Combinatorial probability and the tightness of generalization bounds // Pattern Recognition and Image Analysis. — 2008. — Vol. 18, no. 2. — Pp. 243–259. PDF, 373Kb.
10. Vorontsov K. Tight Bounds for the Probability of Overfitting // Doklady Mathematics, 2009, Vol. 80, No. 3, pp. 793–796. PDF, 192Kb.
11. Vorontsov K. Splitting and Similarity Phenomena in the Sets of Classifiers and Their Effect on the Probability of Overfitting // Pattern Recognition and Image Analysis, 2009, Vol. 19, No. 3, pp. 412–420. PDF, 164Kb.
12. Vorontsov K. Exact Combinatorial Bounds on the Probability of Overfitting for Empirical Risk Minimization // Pattern Recognition and Image Analysis, 2010, Vol. 20, No. 3, pp. 269–285. PDF, 427Kb.
13. Vorontsov K., Ivahnenko A., Botov P., Reshetnyak I., Tolstikhin I. Combinatorial generalization bounds. 2011. PDF, 315Kb (unpublished).
14. Vorontsov K., Ivahnenko A. Tight Combinatorial Generalization Bounds for Threshold Conjunction Rules // Lecture Notes on Computer Science. 4th International Conference on Pattern Recognition and Machine Intelligence (PReMI’11), Russia, Moscow, June 27–July 1, 2011. Pp 66–73. PDF, 153Kb.
15. Spirin N., Vorontsov K. Learning to Rank with Nonlinear Monotonic Ensemble // Lecture Notes on Computer Science. 10th International Workshop on Multiple Classidier Systems (MCS-10). Naples, Italy, June 15–17, 2011. Pp. 16–25. PDF, 490Kb.
16. Potapenko A. A., Vorontsov K. V. Robust PLSA Performs Better Than LDA // 35th European Conference on Information Retrieval, ECIR-2013, Moscow, Russia, 24–27 March 2013. — Lecture Notes in Computer Science (LNCS), Springer Verlag-Germany, 2013. Pp. 784–787. PDF, 160Kb — poster: PDF, 1Mb.
17. Vorontsov K. V. Additive Regularization for Topic Models of Text Collections // Doklady Mathematics. 2014, Pleiades Publishing, Ltd. — Vol. 89, No. 3, pp. 301–304. PDF, 180Kb.
18. Vorontsov K. V., Potapenko A. A. Tutorial on Probabilistic Topic Modeling: Additive Regularization for Stochastic Matrix Factorization // AIST’2014, Analysis of Images, Social networks and Texts. Springer International Publishing Switzerland, 2014. Communications in Computer and Information Science (CCIS). Vol. 436. pp. 29–46. PDF, 470Kb.
19. Uspenskiy V. M., Vorontsov K. V., Tselykh V. R., Bunakov V. A. Information Function of the Heart: Discrete and Fuzzy Encoding of the ECG-Signal for Multidisease Diagnostic System // in Advances in Mathematical and Computational Tools in Metrology and Testing X (vol.10), Series on Advances in Mathematics for Applied Sciences, vol. 86, World Scientific, Singapore (2015) pp 377-384.
20. Vorontsov K. V., Potapenko A. A. Additive Regularization of Topic Models // Machine Learning. Special Issue “Data Analysis and Intelligent Optimization with Applications”: Volume 101, Issue 1 (2015), Pp. 303-323.
21. Vorontsov K. V., Potapenko A. A., Plavin A. V. Additive Regularization of Topic Models for Topic Selection and Sparse Factorization // The Third International Symposium On Learning And Data Sciences (SLDS 2015). April 20-22, 2015. Royal Holloway, University of London, UK. Springer International Publishing Switzerland 2015, A. Gammerman et al. (Eds.): SLDS 2015, LNAI 9047, pp. 193–202, 2015.
22. Vorontsov K. V., Frei O. I., Apishev M. A., Romov P. A., Suvorova M. A. BigARTM: Open Source Library for Regularized Multimodal Topic Modeling of Large Collections // AIST’2015, Analysis of Images, Social Networks and Texts. Springer International Publishing Switzerland, 2015. Communications in Computer and Information Science (CCIS), pp. 370–384.
23. Vorontsov K. V., Frei O. I., Apishev M. A., Romov P. A., Suvorova M. A., Yanina A. O. Non-Bayesian Additive Regularization for Multimodal Topic Modeling of Large Collections // Proceedings of the 2015 Workshop on Topic Models: Post-Processing and Applications, October 19, 2015, Melbourne, Australia. ACM, New York, NY, USA. pp. 29–37.
24. Apishev M., Koltcov S., Koltsova O., Nikolenko S., Vorontsov K. Mining Ethnic Content Online with Additively Regularized Topic Models. Computación y Sistemas, Vol. 20, No. 3, 2016, pp. 387–403.
25. Apishev M., Koltcov S., Koltsova O., Nikolenko S., Vorontsov K. Additive Regularization for Topic Modeling in Sociological Studies of User-Generated Texts. 15-th Mexican International Conference on Artificial Intelligence. October 23–29, Cancún, Mexico.
26. Chirkova N. A., Vorontsov K. V. Additive Regularization for Hierarchical Multimodal Topic Modeling // Journal Machine Learning and Data Analysis. 2(2), pp. 187-200. 2016.