Ekaterina Lobacheva
- Senior Lecturer:Faculty of Computer Science / Big Data and Information Retrieval School
- Ekaterina Lobacheva has been at HSE University since 2014.
Responsibilities
Deputy head of the Centre of Deep Learning and Bayesian Methods. To conduct a research for Samsung-HSE Laboratory.
Courses (2022/2023)
- Research Seminar "Machine Learning and Applications 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Rus
- Past Courses
Courses (2021/2022)
- Bayesian Methods for Machine Learning (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Rus
- Research Seminar "Machine Learning and Applications" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Rus
- Research Seminar "Machine Learning and Applications 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Rus
Courses (2020/2021)
- Bayesian Methods for Machine Learning (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Rus
- Research Seminar "Machine Learning and Applications" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Rus
Courses (2019/2020)
- Bayesian Methods for Machine Learning (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Rus
- Neurobayesian Models (Master’s programme; Faculty of Computer Science; 2 year, 3 module)Eng
Courses (2018/2019)
Dissertation for a degree of Candidate of Science
E. Lobacheva Deep learning architectures on a limited memory budget
Publications15
- Chapter Kodryan M., Lobacheva E., Nakhodnov M., Vetrov D. Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes, in: Thirty-Sixth Conference on Neural Information Processing Systems : NeurIPS 2022. Curran Associates, Inc., 2022. P. 14058-14070.
- Chapter Sadrtdinov I., Chirkova N., Lobacheva E. On the Memorization Properties of Contrastive Learning, in: ICML 2021 Workshop, Overparameterization: Pitfalls & Opportunities. , 2021.
- Chapter Lobacheva E., Kodryan M., Chirkova N., Malinin A., Vetrov D. On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay, in: Advances in Neural Information Processing Systems 34 (NeurIPS 2021). Curran Associates, Inc., 2021. P. 21545-21556.
- Chapter Lobacheva E., Chirkova N., Kodryan M., Vetrov D. On Power Laws in Deep Ensembles, in: Advances in Neural Information Processing Systems 33 (NeurIPS 2020). Curran Associates, Inc., 2020. P. 2375-2385.
- Chapter Lobacheva E., Chirkova N., Markovich A., Vetrov D. Structured Sparsification of Gated Recurrent Neural Networks, in: Thirty-Fourth AAAI Conference on Artificial Intelligence Vol. 34. Palo Alto, California USA: AAAI Press, 2020. Ch. 5938. P. 4989-4996. doi
- Chapter Lobacheva E., Chirkova N., Markovich A., Vetrov D. Structured Sparsification of Gated Recurrent Neural Networks, in: Workshop on Context and Compositionality in Biological and Artificial Neural Systems, Thirty-third Conference on Neural Information Processing Systems. Vancouver : , 2019. P. 1-4.
- Chapter Chirkova N., Lobacheva E., Vetrov D. Bayesian Compression for Natural Language Processing, in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2018. P. 2910-2915.
- Chapter Lobacheva E., Chirkova N., Vetrov D. Bayesian Sparsification of Gated Recurrent Neural Networks, in: Workshop on Compact Deep Neural Network Representation with Industrial Applications, Thirty-second Conference on Neural Information Processing Systems. Montréal : , 2018. P. 1-6.
- Chapter Chistyakov A., Lobacheva E., Shevelev A., Romanenko A. Monotonic models for real-time dynamic malware detection, in: Workshop of the 6th International Conference on Learning Representations (ICLR). International Conference on Learning Representations, ICLR, 2018. P. 1-6.
- Chapter Lobacheva E., Chirkova N., Vetrov D. Bayesian Sparsification of Recurrent Neural Networks, in: 1st Workshop on Learning to Generate Natural Language, International Conference on Machine Learning. , 2017. P. 1-8.
- Chapter Chistyakov A., Lobacheva E., Kuznetsov A., Romanenko A. Semantic embeddings for program behaviour patterns, in: Workshop of the 5th International Conference on Learning Representations (ICLR). , 2017. P. 1-4.
- Chapter Kirillov A., Gavrikov M., Lobacheva E., Osokin A., Vetrov D. Deep Part-Based Generative Shape Model with Latent Variables, in: Proceedings of the 27th British Machine Vision Conference. -, 2016. P. 1-12. doi
- Chapter Lobacheva E., Veksler O., Boykov Y. Joint Optimization of Segmentation and Color Clustering, in: Proceedings of the 2015 IEEE International Conference on Computer Vision. Los Alamitos, Washington, Tokyo : IEEE Computer Society, 2015. P. 1626-1634. doi
- Article Кириллов А. Н., Гавриков М. И., Лобачева Е. М., Осокин А. А., Ветров Д. П. Многоклассовая модель формы со скрытыми переменными // Интеллектуальные системы. Теория и приложения. 2015. Т. 19. № 2. С. 75-95.
- Article Lobacheva E. Automated real-time classification of functional states based on physiological parameters // Procedia - Social and Behavioral Sciences. 2013. Vol. 86 . P. 373-378.
HSE University Faculty of Computer Science Holds Meetup on Data Science in Yerevan
In late April, the HSE University Faculty of Computer Science organised its first data science meetup in the capital of Armenia together with the Russian-Armenian University (RAU). The event featured speakers from HSE University, Yandex, and SberDevices. The meeting featured the participation of students from Yerevan universities who have recently become acquainted with data science, as well as specialists in the field.
17 Articles by Researchers of HSE Faculty of Computer Science Accepted at NeurIPS
In 2022, 17 articles by the researchers of HSE Faculty of Computer Science were accepted at the NeurIPS (Conference and Workshop on Neural Information Processing Systems), one of the world’s most prestigious events in the field of machine learning and artificial intelligence. The 36th conference will be held in a hybrid format from November 28th to December 9th in New Orleans (USA).
Faculty Submits Ten Papers to NeurIPS 2021
35th Conference on Neural Information Processing Systems (NeurIPS 2021) is one of the world's largest conferences on machine learning and neural networks. It takes place on December 6-14, 2021.
NeurIPS — 2020 Accepts Three Articles from Faculty of Computer Science’s Researchers
34th conference on neural information processing systems NeurIPS 2020 is one of the largest conferences on machine learning in the world, taking place since 1989. It was going to take place in Vancouver, Canada on December 6-12, but takes place online.NeurIPS is as prestigious as ever, with 9,454 articles submitted and 1,300 articles accepted by the conference. Among those accepted are three articles by the researchers of the Faculty of Computer Science:
The paper "On Power Laws in Deep Ensembles" accepted as a spotlight to NeurIPS'20
Устный доклад сотрудников Лаборатории на одной из крупнейших конференций по ИИ.
The faculty presented the results of their research at the largest international machine learning conference NeurIPS
Researchers of the Faculty of Computer Science presented their papers at the annual conference of Neural Information Processing Systems (NeurIPS), which was held from 2 to 8 December 2018 in Montreal, Canada.
Faculty of Computer Science Staff Attend International Conference on Machine Learning
On August 6-11 the 34th International Conference on Machine Learning was held in Sydney, Australia. This conference is ranked A* by CORE, and is one of two leading conferences in the field of machine learning. It has been held annually since 2000, and this year, more than 1,000 participants from different countries took part.
Reports by Ekateina Lobacheva and Dmitry Vetrov Accepted at ICCV 2015
The reports be Ekateina Lobacheva, doctoral student, and Dmitry Vetrov, Associate Professor of the Department Dmitry Vetrov, Associate Professor at the Big Data and Information Retrieval School were accepted the organisers of the International Conference on Computer Vision, which got the highest rank A* according to the international rating of IT conferences.