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Найдены 30 853 публикации
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Natalia Loukachevitch, Nokel M. In bk.: Proceedings 10th International Conference on Terminology and Artificial Intelligence TIA 2013. P.: Université Paris 13 - Paris Sorbonne Cité, 2013. P. 69-76.
Добавлено: 18 декабря 2014
Глава
Knyazev M. In bk.: Proceedings of the 26th Meeting of Formal Approaches to Slavic Linguistics. Michigan Slavic Publications, 2018.
Добавлено: 19 апреля 2018
Глава
Nenova Elena, Ignatov D. I., Konstantinov A. V. In bk.: Formal Concept Analysis Meets Information Retrieval 2013. Vol. 977. Aachen: CEUR Workshop Proceedings, 2013. P. 57-73.

We propose a new approach for Collaborative ltering which is based on Boolean Matrix Factorisation (BMF) and Formal Concept Analysis. In a series of experiments on real data (Movielens dataset) we compare the approach with the SVD- and NMF-based algorithms in terms of Mean Average Error (MAE). One of the experimental con- sequences is that it is enough to have a binary-scaled rating data to obtain almost the same quality in terms of MAE by BMF than for the SVD-based algorithm in case of non-scaled data.

Добавлено: 10 октября 2013
Глава
Kozintseva E., Dragoy O., Ivanova M. et al. In bk.: Proceedings of the Sixth International Conference on Cognitive Science. 2014. P. 64-65.
Добавлено: 6 июня 2016
Глава
Efimov E., Shevgunov T., Filimonova D. In bk.: 2016 17th International Radar Symposium (IRS). IEEE, 2016. P. 1-3.
Добавлено: 5 мая 2019
Глава
Sorlin S., Lajus J. In bk.: Media and the Politics of Arctic Climate Change: When the Ice Breaks. NY: Palgrave Macmillan, 2013. Ch. 4. P. 70-92.
Добавлено: 17 ноября 2013
Глава
Руденко В. А. В кн.: Материалы XIII международной научно-практической конференции «Наука в современном информационном обществе», 3-4 октября 2017 г., North Charleston. Научно-издательский центр Академический, 2017. С. 101-103.

Согласно современным исследованиям учет возможной зависимости случайных составляющих ошибки в модели стохастической производственной функции позволяет улучшить качество оценок параметров моделей. Доказано, что для этого можно использовать аппарат копула-функций, позволяющий описать зависимость компонент ошибки с помощью некоторой фиксированной копулы, выбор которой должен быть обусловлен целями исследования.В данной работе особое внимание будет уделено случаю наличия информации о факторах эффективности и показано влияние включения факторов эффективности в модель на зависимость случайных составляющих ошибки.

Добавлено: 21 ноября 2018
Глава
Евсютин О. О., Мещеряков Р. В., Югов Н. Т. et al. In bk.: 2017 Second Russia and Pacific Conference on Computer Technology and Applications (RPC). IEEE, 2017. P. 49-53.
Добавлено: 8 сентября 2019
Глава
Vereshchagin N. In bk.: 8th International Computer Science Symposium in Russia. Berlin: Springer, 2013. P. 203-2011.

Assume that $\NP\not\subset\RP$. Gutfreund, Shaltiel, and Ta-Shma in [Computational Complexity 16(4):412-441 (2007)] have proved that for every randomized polynomial time decision algorithm $D$ for SAT there is a polynomial time samplable distribution such that $D$ errs with probability at least $1/6-\eps$ on a random formula chosen with respect to that distribution. A challenging problem is to increase the error probability to the maximal possible $1/2-\eps$ (the random guessing has success probability 1/2). In this paper, we make a small step towards this goal: we show how to increase the error probability to $1/3-\eps$.

Добавлено: 14 декабря 2013
Глава
Makhalova T., Nourine L. In bk.: Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.. Vol. 1921. CEUR-WS.org, 2017.
Добавлено: 10 октября 2017
Глава
Dominguez Espinosa A., He J., Rosabal-Coto M. et al. In bk.: Venture into cross-cultural psychology: Proceedings from the 23rd Congress of the International Association for Cross-Cultural Psychology.. IACCP, 2018. P. 1-12.
Добавлено: 26 октября 2018
Глава
Proskuryakova L. N., Meissner D., Rudnik P. B. In bk.: Strategic Public Private partnerships for STI. OECD, 2016.
Добавлено: 22 сентября 2016
Глава
Sloev I., Lianos G. In bk.: Recent Advances in Game Theory and Applications: European Meeting on Game Theory, Saint Petersburg, Russia, 2015, and Networking Games and Management, Petrozavodsk, Russia, 2015. Switzerland: Birkhauser/Springer, 2016. P. 111-130.
Добавлено: 17 февраля 2017
Глава
Podobryaev Alexander, Ivlieva Natalia, Sudo Y. et al. In bk.: NELS 45: Proceedings of the Forty-Fifth Annual Meeting of the North East Linguistic Society. Amherst: GLSA Publ., 2015. P. 135-144.
Добавлено: 9 октября 2015
Глава
Sergey Efremov, Nikolai Pilipenko, Leonid Voskov. In bk.: Procedia Engineering. Vol. 100: 25th DAAAM International Symposium on Intelligent Manufacturing and Automation, 2014. Switzerland: Elsevier, 2015. P. 1215-1223.
Добавлено: 23 октября 2014
Глава
Lyadova L. N., Sukhov A., Zamyatina E. In bk.: Advances in Information Science and Applications. Volumes I & II. Proceedings of the 18th International Conference on Computers (part of CSCC '14). Vol. 1-2. Santorini Island: CSCC, 2014. P. 421-425.

An approach of using of the DSM-platform MetaLanguage for integration of various modeling systems is presented. This tool allows to design visual domain-specific modeling languages and to create domain models with developed languages. The MetaLanguage system includes components for describing transformations of models from one formal notation to another. Domain-specific modeling permits various specialists to use concepts from different domains at creating and analyzing of models. An integration of DSM-platforms with tools of models analysis allows to involve domain experts, end-users in the process of constructing and analyzing of models; to reduce the complexity of models development; to fulfill research of models from various points of view with usage of various methods and tools.

Добавлено: 26 июля 2014
Глава
Kuzyutin D., Bartel M. In bk.: 2017 Consrtuctive nonsmooth analysis and related topics (dedicated to the memory of V.F.Demyanov) (CNSA). IEEE, 2017. P. 178-181.
Добавлено: 25 декабря 2017
Глава
Belov A. A., Olga G. Andrianova. In bk.: PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE “STABILITY AND OSCILLATIONS OF NONLINEAR CONTROL SYSTEMS” (PYATNITSKIY’S CONFERENCE). IEEE, 2016. P. 1-4.
Добавлено: 6 февраля 2018
Глава
Babenko A., Lempitsky V. In bk.: Proceedings of the IEEE International Conference on Computer Vision (ICCV 2017). Venice: IEEE, 2017. P. 4885-4893.

To compress large datasets of high-dimensional descriptors, modern quantization schemes learn multiple codebooks and then represent individual descriptors as combinations of codewords. Once the codebooks are learned, these schemes encode descriptors independently. In contrast to that, we present a new coding scheme that arranges dataset descriptors into a set of arborescence graphs, and then encodes non-root descriptors by quantizing their displacements with respect to their parent nodes. By optimizing the structure of arborescences, our coding scheme can decrease the quantization error considerably, while incurring only minimal overhead on the memory footprint and the speed of nearest neighbor search in the compressed dataset compared to the independent quantization. The advantage of the proposed scheme is demonstrated in a series of experiments with datasets of SIFT and deep descriptors.

Добавлено: 26 декабря 2017
Глава
Shishkova A., Chernyak E. L. In bk.: CLLS 2016. Computational Linguistics and Language Science. Proceedings of the Workshop on Computational Linguistics and Language Science. Moscow, Russia, April 26, 2016. Vol. 1886. Aachen: CEUR Workshop Proceedings, 2017. P. 42-47.
Добавлено: 10 октября 2017
Глава
Chernyak E. L., Ilvovsky D. In bk.: The 3d International Workshop on Concept Discovery in Unstructured Data (CDUD 2016). Proceedings of the Third Workshop on Concept Discovery in Unstructured Data co-located with the 13th International Conference on Concept Lattices and Their Applications (CLA 2016), Moscow, Russia, July 18, 2016. CEUR Workshop Proceedings. Vol. 1625. Aachen: CEUR Workshop Proceedings, 2016. P. 25-31.

In this paper an extension of tf-idf weighting on annotated suffix tree (AST) structure is described. The new weighting scheme can be used for computing similarity between texts, which can further serve as in input to clustering algorithm. We present preliminary tests of us-ing AST for computing similarity of Russian texts and show slight im-provement in comparison to the baseline cosine similarity after applying spectral clustering algorithm.

Добавлено: 26 октября 2016