Max Ryabinin
- Research Assistant:Faculty of Computer Science / Big Data and Information Retrieval School / Yandex Laboratory
- Max Ryabinin has been at HSE University since 2017.
Courses (2020/2021)
- Deep Learning (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Rus
- Efficient Deep Learning Systems (Optional course (faculty); Faculty of Computer Science; 4 module)Rus
- Past Courses
Courses (2019/2020)
- 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
Publications2
- Chapter Ryabinin M., Liudmila Prokhorenkova, Sergei Popov, Voita E. Embedding Words in Non-Vector Space with Unsupervised Graph Learning, in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics, 2020. P. 7317-7331. doi (in press)
- Chapter Ryabinin M., Gusev A. Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts, in: Advances in Neural Information Processing Systems 33 (NeurIPS 2020). Curran Associates, Inc., 2020. P. 3659-3672.
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:
