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Language Proficiency
English
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Supervisor
D. Vetrov
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Nadezhda Chirkova

  • Nadezhda Chirkova has been at HSE since 2016.

Responsibilities

  • research in the area of recurrent neural networks

Education

2016

Bachelor in Applied Mathematics and Information Science
Lomonosov Moscow State University

Young Faculty Support Program (Group of Young Academic Professionals)
Category "New Researchers" (2018)

Courses (2017/2018)

Courses (2016/2017)

Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Rus

Publications2

Conferences

2016
11-я международная конференция Интеллектуализация обработки информации (Барселона). Presentation: Additive Regularization for Hierarchical Multimodal Topic Modeling

Employment history

Junior machine learning researcher, Antiplagiat JSC, 2016 July→2016 August. Developing a prototype of domain specific search system that incorporates hierarchical topic structure learned from the domain data.

Machine Learning Teacher Assistant, Coursera machine learning specialization, 2016 January→2017 March. Developing practical assignments for the students explaining how machine learning algorithms work.

Timetable for today

Full timetable

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.

'Machine Learning Algorithm Able to Find Data Patterns a Human Could Not'

In December 2016, five new international laboratories opened up at the Higher School of Economics, one of which was the International Laboratory of Deep Learning and Bayesian Methods. This lab focuses on combined neural Bayesian models that bring together two of the most successful paradigms in modern-day machine learning – the neural network paradigm and the Bayesian paradigm.