Участник:Tolstikhin/English

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|'''Tolstikhin Ilya'''
|'''Tolstikhin Ilya'''
PhD student at [[Вычислительный центр РАН|the Dorodnicyn Computing Centre of the Russian Academy of Sciences]].
PhD student at [[Вычислительный центр РАН|the Dorodnicyn Computing Centre of the Russian Academy of Sciences]].
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Developer in [http://ru.wikipedia.org/wiki/Лаборатория_Касперского Kaspersky Lab], detection methods analysis group.
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Senior Research Developer, [http://ru.wikipedia.org/wiki/Лаборатория_Касперского Kaspersky Lab], detection methods analysis group.
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*'''[[Участник:Tolstikhin/Publications|List of publications]]'''.
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*'''[[Участник:Tolstikhin/PublicationsEng|Publications]]'''.
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*'''[[Участник:Tolstikhin/Articles|Recently read articles]]'''.
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*'''[[Участник:Tolstikhin/TODO|TODO]]'''.
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*'''[[Участник:Tolstikhin/TODO|Other materials]]'''.
'''Scientific interests:'''
'''Scientific interests:'''
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*'''''Statistical Learning Theory (SLT)''''';
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*Statistical Learning Theory (SLT);
*generalization and excess risk bounds in SLT;
*generalization and excess risk bounds in SLT;
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*concentration of measure inequalities in probability theory.
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*concentration of measure inequalities in probability theory and applications;
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*empirical processes and applications;
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More information available on th CV page: '''[[Участник:Tolstikhin/CV|CV]]'''.
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*PAC-Bayes bounds and applications in machine learning.
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'''Current activity''':
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More information available on th CV page (in russian): '''[[Участник:Tolstikhin/CV|CV]]'''.
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*[[Предсказывающие_неравенства_в_задаче_эмпирической_минимизации_риска_(виртуальный_семинар)|Discussion of lecture notes by V. Koltchinskii]] about excess risk bounds in machine learning.
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'''[[Служебная:EmailUser/Tolstikhin|Feel free to email me]]'''.
'''[[Служебная:EmailUser/Tolstikhin|Feel free to email me]]'''.

Текущая версия

    Tolstikhin Ilya

PhD student at the Dorodnicyn Computing Centre of the Russian Academy of Sciences.
Senior Research Developer, Kaspersky Lab, detection methods analysis group.


Scientific interests:

  • Statistical Learning Theory (SLT);
  • generalization and excess risk bounds in SLT;
  • concentration of measure inequalities in probability theory and applications;
  • empirical processes and applications;
  • PAC-Bayes bounds and applications in machine learning.

More information available on th CV page (in russian): CV.

Feel free to email me.

Russian version of this web page..

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