Dmitry Kropotov
Cited by
Cited by
Scalable gaussian processes with billions of inducing inputs via tensor train decomposition
P Izmailov, A Novikov, D Kropotov
International Conference on Artificial Intelligence and Statistics, 726-735, 2018
A superlinearly-convergent proximal Newton-type method for the optimization of finite sums
A Rodomanov, D Kropotov
International Conference on Machine Learning, 2597-2605, 2016
Automatic Determination of the Number of Components in the EM Algorithm of Restoration of a Mixture of Normal Distributions
DP Vetrov, DA Kropotov, AA Osokin
Computational Mathematics and Mathematical Physics 50 (4), 733-746, 2010
On one method of non-diagonal regularization in sparse Bayesian learning
D Kropotov, D Vetrov
Proceedings of the 24th international conference on Machine learning, 457-464, 2007
Knowledge representation and acquisition in expert systems for pattern recognition
OM Vasil’ev, DP Vetrov, DA Kropotov
Computational mathematics and mathematical physics 47 (8), 1373-1397, 2007
The Methods of Dependencies Description with the Help of Optimal Multistage Partitioning
OV Senko, AV Kuznetsova, DA Kropotov
Proceedings of the 18th International Workshop on Statistical Modelling …, 2003
Variational segmentation algorithms with label frequency constraints
D Kropotov, D Laptev, A Osokin, D Vetrov
Pattern Recognition and Image Analysis 20 (3), 324-334, 2010
RECOGNITION: A Universal Software System for Recognition, Data Mining, and Forecasting
YI Zhuravlev, VV Ryazanov, OV Senko, AS Biryukov, DP Vetrov, ...
Pattern Recognition and Image Analysis (Advances in Mathematical Theory and …, 2005
Variational relevance vector machine for tabular data
D Kropotov, D Vetrov, L Wolf, T Hassner
Proceedings of 2nd Asian Conference on Machine Learning, 79-94, 2010
3-D mouse brain model reconstruction from a sequence of 2-D slices in application to Allen brain atlas
A Osokin, D Vetrov, D Kropotov
International Meeting on Computational Intelligence Methods for …, 2009
The use of stability principle for kernel determination in relevance vector machines
D Kropotov, D Vetrov, N Ptashko, O Vasiliev
International Conference on Neural Information Processing, 727-736, 2006
The use of bayesian framework for kernel selection in vector machines classifiers
D Kropotov, N Ptashko, D Vetrov
Iberoamerican Congress on Pattern Recognition, 252-261, 2005
The program system for intellectual data analysis, recognition and forecasting
YI Zhuravlev, VV Ryazanov, OV Senko, AS Biryukov, DP Vetrov, ...
WSEAS Transactions on Information Science and Applications 2 (1), 55-58, 2005
A randomized coordinate descent method with volume sampling
A Rodomanov, D Kropotov
SIAM Journal on Optimization 30 (3), 1878-1904, 2020
Automatic determination of the numbers of components in the EM algorithm for the restoration of a mixture of normal distributions
DP Vetrov, DA Kropotov, AA Osokin
Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki 50 (4), 770-783, 2010
General solutions for information-based and Bayesian approaches to model selection in linear regression and their equivalence
D Kropotov, D Vetrov
Pattern Recognition and Image Analysis 19 (3), 447-455, 2009
Decision trees regularization based on stability principle
D Vetrov, D Kropotov, I Tolstov
Pattern Recognition and Image Analysis (Advances in Mathematical Theory and …, 2005
Faster variational inducing input Gaussian process classification
P Izmailov, D Kropotov
arXiv preprint arXiv:1611.06132, 2016
Video tracking and behaviour segmentation of laboratory rodents
E Lomakina-Rumyantseva, P Voronin, D Kropotov, D Vetrov, A Konushin
Pattern Recognition and Image Analysis 19 (4), 616-622, 2009
Automatic segmentation of mouse behavior using hidden Markov model
D Vetrov, D Kropotov, A Konushin, E Lomakina-Rumyantseva, ...
Measuring Behavior 2008, 241, 2008
The system can't perform the operation now. Try again later.
Articles 1–20