Sergey Nikolenko
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2014';
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ML, KFU';
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Game Theory, HSE';
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Mech. Design, HSE';
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ML, CSClub Kazan';
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Game theory, HSE';
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Math. logic, AU';
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Machine learning, STC';
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Machine learning, AU';
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2013';
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Discrete math, HSE';
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Machine learning, STC';
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Math. logic, AU';
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Cryptography, AU';
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2012';
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Machine learning, STC';
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Math. logic, AU';
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Machine learning II, AU';
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Machine learning, AU';
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Machine learning, EMC';
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2011';
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Cryptography, AU';
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Math. logic, AU';
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Machine learning, AU';
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2010';
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Math. logic, AU';
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Machine learning, AU';
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Cryptography, AU';
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2009';
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Crypto in CS Club';
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Statistics';
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Machine learning, AU';
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Cryptography';
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2008';
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Speech recognition';
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MD for CS Club';
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ML for CS Club';
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Mechanism design';
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2007';
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Machine Learning';
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Probabilistic learning';
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External links';
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Google Scholar profile';
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LiveJournal account
nikolenko (in Russian)
Teaching activities
Machine Learning at EMC
This is a course in machine learning presented in 2012 at the St. Petersburg office of EMC. The course is very similar to this one but goes a bit further; this page contains the slides for EMC presentations not included in the AU course (all slides are in Russian).
- 1. Prior distributions. Conjugate priors.
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- 2. Graphical models and the message passing algorithm. Approximate inference.
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- 3. Bayesian rating models, TrueSkill.
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- 4. Latent Dirichlet Allocation. User behaviour models for click logs.
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- 5. Sampling.
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- 6. Reinforcement learning.
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- 7. Recommender systems.
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- Christopher M. Bishop. Pattern Recognition and Machine Learning. Springer, Information Science and Statistics series, 2006.
- Trevor Hastie, Robert Tibshirani, and Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd ed., Springer, 2009.
- David J. C. MacKay. Information Theory, Inference, and Learning Algorithms. Cambridge University Press, 2003.