5–8 October 2015, Berlin, Germany
Yandex School of Data Analysis Conference
Machine Learning: Prospects and Applications

The conference is organised by the Yandex School of Data Analysis and Yandex, sponsored by Yandex Data Factory. Royal Holloway, University of London is the academical partner of the conference.
This is the second conference on machine learning organised by the Yandex School of Data Analysis and this year it will explore the new frontiers and advances in machine learning – its theory, technology, and applications. With scientists and engineers coming from 14 countries, in addition to talks, discussions and poster sessions, this year’s conference will feature a business event aimed at facilitating cooperation between academics and practitioners. The first conference on machine learning organised by the Yandex School of Data Analysis, which took place in Moscow in 2013, focused on the latest developments in big data.

All the conference photos can be found on Flickr.
Over the past few years, deep learning has been gaining popularity among software developers for the extraordinary experimental results it has demonstrated. More importantly, using this approach enabled developers to create simple tools for solving practical problems across multiple industries. A number of speakers at this conference will talk about this approach in their work.
At the same time, Vladimir Vapnik, one of the main developers of Vapnik–Chervonenkis theory, the father of statistical learning theory, and the co-inventor of the Support Vector Machine method, over the course of the past two years, has had tremendous theoretical progress in his breakthrough theory of machine learning, which he called Intelligent Learning. This novel approach will be presented in detail at the conference by the author and his colleagues.
This conference offers a unique opportunity for everyone in attendance to witness first-hand how these two alternative approaches compare and contrast. During a specially organised discussion, we are hoping to open new advantages of both of these approaches and see the power of synergy stemming from their interrelations.
Beside looking at the exciting prospects promised by deep learning and Vapnik’s Intelligent learning, the conference will explore traditional application areas for machine learning, such as computer vision or natural language processing, alongside some relatively recent ones, such as causality modeling. As significant progress has been made in both old and new areas of application for machine learning, some of the most important cases will be presented at this conference.

The main topics

  • Deep Learning
  • Intelligent Learning
  • Discovery of Causality
  • Abstract Convexity
  • Sub-Linear Methods in Data Analysis
  • Quantum Calculation in Machine Learning
  • Text Analysis and Understanding
  • Video, Image and Signal Analysis
  • Application in Physics, Biology, Medicine and Finance

Key Speakers

  • Francis Bach, France
  • Pierre Baldi, USA
  • Li Deng, USA
  • Alexander Gammerman, UK
  • Nathan Intrator, Israel
  • Vadim Levit, Israel
  • Bernhard Schölkopf, Germany
  • Vladimir Vapnik, USA
  • Vladimir Vovk, UK
  • Lior Wolf, Israel