3rd Winter School on Data Analytics (DA 2018)
- Laboratory of Algorithms and Technologies for Network Analysis of National Research University Higher School of Economics (LATNA)
- Keldysh Institute of Applied Mathematics of Russian Academy of Science (IPM)
Sponsors: The winter school is sponsored by INTEL.
Dates: November 28-30, 2018
The target groups of the school are students and young researchers interested in modern trends in data analytics, including big data processing and new machine learning and data mining techniques.
Student session: a student session is planned where motivated students can present the results of their research to internationally recognized experts
Registration Deadline: October 31
Contact: Sergey Slashchinin (email@example.com)
Arseni Ashukha, Samsung AI Center, Moscow, University of Amsterdam
Lecture 1 - Introduction to Bayesian Machine Learning
Lecture 2 - Bayesian Deep learning
Mario Guarracino, ICAR-CNR, Italy
Lecture 1 - Robust Data Analytics
Lecture 2 - Robust generalized eigenvalue classifier with ellipsoidal uncertainty
Seminar - Supervised classification of network data
Viktor Lempitsky, Samsung AI Center and Skoltech
Lectures 1&2 - Generative convolutional networks: a short survey
Panos Pardalos , University of Florida, USA and HSE NN
Lecture - Network Analysis, Data Sciences and Control in Computational NeuroScience
Oleg Prokopyev University of Pittsburg , USA and HSE NN
Lecture - A mixed-integer fractional optimization approach to best subset selection
Varvara Rasskazova, Moscow Aviation Institute
Lecture 1 - Maximum Independent Set Problem (MISP)
Lecture 2 - Effective Methods for MISP
Andrey Savchenko , National Research University Higher School of Economics, Nizhny Novgorod
Lecture - Facial analytics in mobile applications
Rostislav Yavorsky, National Research University Higher School of Economics, Moscow
Lecture 1 - How to build and analyze a simple social graph with yEd Graph Editor
Lecture 2- Different extensions and modifications of the social graph
Lecture 3 - Research challenges of corporate networks analysis
Co-Chairs of the school:
Local Organizing Committee:
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