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International Workshop on Statistical Learning
(June 26–28, 2013)

The field of statistical learning theory has grown far beyond the traditional regression and classification problems. The purpose of this workshop is to bring together leading researchers who are drawing the new frontiers of this ever growing field. Problems that will be discussed include: supervised and unsupervised learning, learning on graphs and networks, sequential learning, high-dimensional learning, etc.

E-mail:
Website: https://www.stat.iitp.ru

Institutions
Research laboratory in Predictive Modeling and Optimization at PhysTech (PreMoLab), Moscow
Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), Moscow


International Workshop on Statistical Learning, June 26–28, 2013

June 26, 2013 (Wed)
1. Matrix concentration inequalities via the method of exchangeable pairs
M. I. Jordan
June 26, 2013 10:00–10:30 		M. I. Jordan
  
2. Estimation and variable selection with exponential weights
K. Lounici
June 26, 2013 10:30–11:00 		K. Lounici
  
3. Deep neural network learning by scattering
S. G. Mallat
June 26, 2013 11:30–12:00 		S. G. Mallat
  
4. An optimal affine invariant smooth minimization algorithm
A. D'Aspremont
June 26, 2013 12:00–12:30 		A. D'Aspremont
  
5. The development of semidefinite sparse component analysis
E. Diederichs
June 26, 2013 14:00–14:30 		E. Diederichs
  
6. Empirical entropy, minimax regret and minimax risk
A. Tsybakov
June 26, 2013 14:30–15:00 		A. Tsybakov
  
7. Lipschitz optimization with noisy 0th order information
S. Bubeck
June 26, 2013 15:30–16:00 		S. Bubeck
  
8. Generalized exponential weight algorithm and applications to online learning
V. Perchet
June 26, 2013 16:00–16:30 		V. Perchet
  

June 27, 2013 (Thu)
9. On estimation of sparse eigenvectors in high dimensions
B. Nadler
June 27, 2013 10:00–10:30 		B. Nadler
  
10. Nonparametric testing by convex optimization
A. B. Yuditskii
June 27, 2013 10:30–11:00 		A. B. Yuditskii
  
11. Dimension free PAC-Bayes bounds and unsupervised classification
O. Catoni
June 27, 2013 11:30–12:00 		O. Catoni
  
12. Robust clustering using adaptive weights
V. G. Spokoiny
June 27, 2013 12:00–12:30 		V. G. Spokoiny
  
13. A new method in adaptive estimation
O. V. Lepskiĭ
June 27, 2013 14:00–14:30 		O. V. Lepskiĭ
  
14. Classification of sparse high-dimensional vectors
Ch. Pouet
June 27, 2013 14:30–15:00 		Ch. Pouet
  
15. Sparse regression under heteroskedasticity and group sparsity
A. S. Dalalyan
June 27, 2013 15:30–16:00 		A. S. Dalalyan
  
16. Model selection in sparse heterogeneous framework
L. Cavalier
June 27, 2013 16:00–16:30 		L. Cavalier
  
17. Limits of local algorithms for sparse random graphs
D. Gamarnik
June 27, 2013 16:30–17:00 		D. Gamarnik
  

June 28, 2013 (Fri)
18. An application of the Foster–Vohra method of calibration to stock market games
V. V. V'yugin
June 28, 2013 10:00–10:30 		V. V. V'yugin
  
19. Combinatorial theory of overfitting
K. V. Vorontsov
June 28, 2013 10:30–11:00 		K. V. Vorontsov
  
20. Asymptotically optimal method for manifold estimation problem
Yu. A. Yanovich
June 28, 2013 11:30–12:00 		Yu. A. Yanovich
  
21. Disentangling mixtures of Gaussians
A. Moitra
June 28, 2013 12:00–12:30 		A. Moitra
  
 
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