Участник:Vokov/Publications

Материал из MachineLearning.

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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.
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. 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.
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.
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. Advances in Computational Intelligence, 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Quintana Roo, Mexico, October 23–29, 2016. Proceedings, Part I. Lecture Notes in Artificial Intelligence, Volume 10061, pp. 166–181.
26. Chirkova N., Vorontsov K. Additive Regularization for Hierarchical Multimodal Topic Modeling // Journal Machine Learning and Data Analysis. 2(2), pp. 187-200. 2016.
27. Ianina A., Golitsyn L., Vorontsov K. Multi-objective topic modeling for exploratory search in tech news // Filchenkov A., Pivovarova L., Žižka J. (eds) Artificial Intelligence and Natural Language. AINL 2017, St. Petersburg, Russia, September 20-23, 2017. — Communications in Computer and Information Science, vol 789. Springer, Cham, 2017. — pp 181–193.
28. Potapenko A. A., Popov A. S., Vorontsov K. V. Interpretable probabilistic embeddings: bridging the gap between topic models and neural networks // Filchenkov A., Pivovarova L., Žižka J. (eds) Artificial Intelligence and Natural Language. AINL 2017, St. Petersburg, Russia, September 20-23, 2017. — Communications in Computer and Information Science, vol 789. Springer, Cham, 2017. — pp 167-180.
29. Kochedykov D., Apishev M., Golitsyn L., Vorontsov K. Fast and Modular Regularized Topic Modelling // Proceeding Of The 21St Conference Of FRUCT (Finnish-Russian University Cooperation in Telecommunications) Association. The seminar on Intelligence, Social Media and Web (ISMW). Helsinki, Finland, November 6-10, 2017. Pp.182–193.
30. Alekseev V. A., Bulatov V. G., Vorontsov K. V. Intra-Text Coherence as a Measure of Topic Models Interpretability // Computational Linguistics and Intellectual Technologies. Dialogue 2018. Pp. 1-13.
31. Belyy A. V., Seleznova M. S., Sholokhov A. K., Vorontsov K. V. Quality Evaluation and Improvement for Hierarchical Topic Modeling // Computational Linguistics and Intellectual Technologies. Dialogue 2018. Pp. 110-123.
32. Skachkov N. A., Vorontsov K. V. Improving topic models with segmental structure of texts // Computational Linguistics and Intellectual Technologies. Dialogue 2018. Pp. 652-661.
33. Karabulatova I., Vorontsov K. Digital linguistical migrationology: the possibilities of artificial intelligence in the study of migration processes // Proceedings of 2nd World congress in real and virtual mode «East-west: the intersection of cultures», Kyoto Sangyo University, October 2–6, 2019. Vol.2, Pp. 760–765.
34. Soboleva D., Vorontsov K. Three-stage question answering system with sentence ranking // Proceedings of 3rd Workshop «Computational linguistics and language science», vol. 4, Pp. 18–25.
35. Ianina A., Vorontsov K. Regularized Multimodal Hierarchical Topic Model for Document-by-Document Exploratory Search // Proceeding Of The 25th Conference Of FRUCT (Finnish-Russian University Cooperation in Telecommunications) Association. The seminar on Intelligence, Social Media and Web (ISMW). Helsinki, Finland, November 5-8, 2019. Pp.131–138.
36. Eremeev M., Vorontsov K. Lexical Quantile-Based Text Complexity Measure // Proceedings of Recent Advances in Natural Language Processing, Varna, Bulgaria, Sep 2–4 2019. Pp. 270–275.
37. Egorov E., Nikitin F., Goncharov A., Alekseev V., Vorontsov K. Topic Modelling for Extracting Behavioral Patterns from Transactions Data // IC-AIAI 2019.
38. Apishev M., Vorontsov K. Learning Topic Models with Arbitrary Loss // 26th Conference of Open Innovations Association (FRUCT). 2020. Pp. 30–37.
39. Eremeev M. A., Vorontsov K. V. Quantile-based approach to estimating cognitive text complexity // Computational Linguistics and Intellectual Technologies. Dialogue 2020. Pp. 241–254.
40. Feldman D. G., Sadekova T. R., Vorontsov K. V. Combining Facts, Semantic Roles and Sentiment Lexicon in A Generative Model for Opinion Mining // Computational Linguistics and Intellectual Technologies. Dialogue 2020. Pp. 268–283.
41. Veselova E., Vorontsov K. Topic Balancing with Additive Regularization of Topic Models // Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, July 5 - July 10, 2020. Pp. 59–65.
42. Ianina A., Vorontsov K. Hierarchical Interpretable Topical Embeddings for Exploratory Search and Real-Time Document Tracking. International Journal of Embedded and Real-Time Communication Systems (IJERTCS) Vol.11, Issue 4, 2020. 19p.
43. Irkhin I. A., Bulatov V. G., Vorontsov K. V. Additive regularization of topic models with fast text vectorization // Computer Research and Modeling, 2020, 12(6), Pp.1515–1528.
44. Irkhin I. A., Vorontsov K. V. Convergence of the algorithm of additive regularization of topic models // Trudy Instituta Matematiki i Mekhaniki UrO RAN, 2020, 26(3), Pp.56–68.
45. Ishkina S. K., Vorontsov K. V. Sharpness Estimation of Combinatorial Generalization Ability Bounds for Threshold Decision Rules // Automation and Remote Control, 2021, 82(5), Pp.863–876.
46. Alekseev V., Egorov E., Vorontsov K., Goncharov A., Nurumov K., Buldybayev T. TopicBank: Collection of coherent topics using multiple model training with their further use for topic model validation // Data and Knowledge Engineering, 2021. V.135, 101921.
47. Grishanov A., Ianina A., Vorontsov K. Multiobjective Evaluation of Reinforcement Learning Based Recommender Systems // Proceedings of the 16th ACM Conference on Recommender Systems. 2022. Pp. 622–627.
48. Vorontsov K. V. Rethinking Probabilistic Topic Modeling from the Point of View of Classical Non-Bayesian Regularization // Data Science and Optimization, Springer, 2023.