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Vadim Mottl
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2020 – today
- 2021
- [c49]Alexey Morozov, Brian Angulo, Vadim Mottl, Alexander Tatarchuk, Olga Krasotkina:
Differential Leave-One-Out Cross-Validation for Feature Selection in Generalized Linear Dependence Models. ITCC 2021: 47-56
2010 – 2019
- 2019
- [c48]Valentina Sulimova, Sergey Bukhonov, Olga Krasotkina, Vadim Mottl, Annette Sterr, Kevin Wells, David Windridge:
Sparse Multimodal Classification of EEG Signals from Rapid Serial Visual Presentation of Diagnostic Images. MLDM (1) 2019: 355-366 - [c47]Vadim Mottl, Olga Krasotkina, Valentina Sulimova, Alexey Morozov, Ilya Pugach, Alexander Tatarchuk:
Linear complexity algorithms for high dimensional SVM and regression problems with smart sparse regularization. MLDM (1) 2019: 412-430 - 2018
- [c46]Valentina Sulimova, Alexander Zhukov, Olga Krasotkina, Vadim Mottl, Anatoly Markov
:
Automatic Rail Flaw Localization and Recognition by Featureless Ultrasound Signal Analysis. MLDM (1) 2018: 16-27 - [c45]Olga Krasotkina, Michael Markov, Vadim Mottl, Ilya Pugach, Dmitry Babichev, Alexey Morozov:
Constrained Regularized Regression Model Search in Large Sets of Regressors. MLDM (2) 2018: 394-408 - 2017
- [c44]Valentina Sulimova, Vadim Mottl:
Potential Functions for Signals and Symbolic Sequences. Braverman Readings in Machine Learning 2017: 3-31 - [c43]Vadim Mottl, Oleg Seredin, Olga Krasotkina:
Compactness Hypothesis, Potential Functions, and Rectifying Linear Space in Machine Learning. Braverman Readings in Machine Learning 2017: 52-102 - [c42]Olga Krasotkina, Vadim Mottl, Michael Markov, Elena Chernousova, Dmitry Malakhov:
Methods of Hyperparameter Estimation in Time-Varying Regression Models with Application to Dynamic Style Analysis of Investment Portfolios. MLDM 2017: 431-450 - 2016
- [c41]Anton Malenichev, Olga Krasotkina, Vadim Mottl, Oleg Seredin:
Multi-class Classification in Big Data. AIST (Supplement) 2016: 203-211 - [c40]Valentina Sulimova, Oleg Seredin, Vadim Mottl:
Recognition of Herpes Viruses on the Basis of a New Metric for Protein Sequences. IDP 2016: 61-73 - [c39]Pavel A. Turkov, Olga Krasotkina, Vadim Mottl, Alexey Sychugov:
Feature Selection for Handling Concept Drift in the Data Stream Classification. MLDM 2016: 614-629 - [c38]Zhosan Yulia, Olga Krasotkina, Vadim Mottl:
Sparse logistic regression with supervised selectivity for predictors selection in credit scoring. SoICT 2016: 167-172 - 2015
- [c37]Olga Krasotkina, Oleg Seredin
, Vadim Mottl:
Supervised Selective Combination of Diverse Object-Representation Modalities for Regression Estimation. MCS 2015: 89-99 - [c36]Olga Krasotkina, Vadim Mottl:
A Bayesian Approach to Sparse Learning-to-Rank for Search Engine Optimization. MLDM 2015: 382-394 - [c35]Olga Krasotkina, Vadim Mottl:
A Bayesian Approach to Sparse Cox Regression in High-Dimentional Survival Analysis. MLDM 2015: 425-437 - 2014
- [c34]Elena Chernousova, Pavel Levdik, Alexander Tatarchuk, Vadim Mottl, David Windridge
:
Non-enumerative Cross Validation for the Determination of Structural Parameters in Feature-Selective SVMs. ICPR 2014: 3654-3659 - [c33]Anna Gubareva, Valentina Sulimova, Oleg Seredin
, Aleksandr Larin, Vadim Mottl:
Finding the Largest Hypercavity in a Linear Data Space. ICPR 2014: 4406-4410 - [c32]Anton Malenichev, Valentina Sulimova, Olga Krasotkina, Vadim Mottl, Anatoly Markov
:
An Automatic Matching Procedure of Ultrasonic Railway Defectograms. MLDM 2014: 315-327 - [c31]Alexander Tatarchuk, Valentina Sulimova, Ivan Yu. Torshin
, Vadim Mottl, David Windridge
:
Supervised Selective Kernel Fusion for Membrane Protein Prediction. PRIB 2014: 98-109 - 2013
- [c30]Pavel A. Turkov, Olga Krasotkina, Vadim Mottl:
Dynamic Programming for Bayesian Logistic Regression Learning under Concept Drift. PReMI 2013: 190-195 - 2012
- [c29]Oleg Seredin, Vadim Mottl, Alexander Tatarchuk, Nikolay Razin, David Windridge:
Convex support and Relevance Vector Machines for selective multimodal pattern recognition. ICPR 2012: 1647-1650 - [c28]Pavel A. Turkov, Olga Krasotkina, Vadim Mottl:
The Bayesian logistic regression in pattern recognition problems under concept drift. ICPR 2012: 2976-2979 - [c27]Pavel A. Turkov, Olga Krasotkina, Vadim Mottl:
Bayesian Approach to the Concept Drift in the Pattern Recognition Problems. MLDM 2012: 1-10 - [c26]Nikolay Razin, Dmitry Sungurov, Vadim Mottl, Ivan Yu. Torshin
, Valentina Sulimova, Oleg Seredin
, David Windridge
:
Application of the Multi-modal Relevance Vector Machine to the Problem of Protein Secondary Structure Prediction. PRIB 2012: 153-165 - 2011
- [c25]Maxim Panov
, Alexander Tatarchuk, Vadim Mottl, David Windridge
:
A Modified Neutral Point Method for Kernel-Based Fusion of Pattern-Recognition Modalities with Incomplete Data Sets. MCS 2011: 126-136 - [c24]Olga Krasotkina, Vadim Mottl, Pavel A. Turkov:
Bayesian Approach to the Pattern Recognition Problem in Nonstationary Environment. PReMI 2011: 24-29 - 2010
- [j2]Norman Poh, David Windridge
, Vadim Mottl, Alexander Tatarchuk, Andrey Eliseyev
:
Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution. IEEE Trans. Inf. Forensics Secur. 5(3): 461-469 (2010) - [c23]Andrey Kopylov
, Olga Krasotkina, Oleksandr Pryimak, Vadim Mottl:
A Signal Processing Algorithm Based on Parametric Dynamic Programming. ICISP 2010: 280-286 - [c22]Alexander Tatarchuk, Eugene Urlov, Vadim Mottl, David Windridge
:
A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities. MCS 2010: 165-174 - [c21]Valentina Sulimova, Nikolay Razin, Vadim Mottl, Ilya B. Muchnik, Casimir A. Kulikowski:
A Maximum-Likelihood Formulation and EM Algorithm for the Protein Multiple Alignment Problem. PRIB 2010: 171-182
2000 – 2009
- 2009
- [j1]Oleg Seredin, Andrey Kopylov, Vadim Mottl:
Selection of Subsets of Ordered Features in Machine Learning. Trans. Mach. Learn. Data Min. 2(2): 65-79 (2009) - [c20]Valentina Sulimova, Vadim Mottl, Boris G. Mirkin
, Ilya B. Muchnik, Casimir A. Kulikowski:
A Class of Evolution-Based Kernels for Protein Homology Analysis: A Generalization of the PAM Model. ISBRA 2009: 284-296 - [c19]David Windridge
, Norman Poh, Vadim Mottl, Alexander Tatarchuk, Andrey Eliseyev
:
Handling Multimodal Information Fusion with Missing Observations Using the Neutral Point Substitution Method. MCS 2009: 161-170 - [c18]Alexander Tatarchuk, Valentina Sulimova, David Windridge
, Vadim Mottl, Mikhail Lange:
Supervised Selective Combining Pattern Recognition Modalities and Its Application to Signature Verification by Fusing On-Line and Off-Line Kernels. MCS 2009: 324-334 - [c17]Oleg Seredin
, Andrey Kopylov
, Vadim Mottl:
Selection of Subsets of Ordered Features in Machine Learning. MLDM 2009: 16-28 - 2008
- [c16]Olga Krasotkina, Vadim Mottl:
Adaptive nonstationary regression analysis. ICPR 2008: 1-4 - [c15]Vadim Mottl, Mikhail Lange, Valentina Sulimova, Alexey Yermakov:
Signature verification based on fusion of on-line and off-line kernels. ICPR 2008: 1-4 - [c14]Alexander Tatarchuk, Vadim Mottl, Andrey Eliseyev
, David Windridge
:
Selectivity supervision in combining pattern-recognition modalities by feature- and kernel-selective support vector machines. ICPR 2008: 1-4 - 2007
- [c13]Vadim Mottl, Alexander Tatarchuk, Valentina Sulimova, Olga Krasotkina, Oleg Seredin:
Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion. MCS 2007: 1-12 - [c12]David Windridge
, Vadim Mottl, Alexander Tatarchuk, Andrey Eliseyev
:
The Neutral Point Method for Kernel-Based Combination of Disjoint Training Data in Multi-modal Pattern Recognition. MCS 2007: 13-21 - 2005
- [c11]Vadim Mottl, Olga Krasotkina, Oleg Seredin, Ilya B. Muchnik:
Principles of Multi-kernel Data Mining. MLDM 2005: 52-61 - 2004
- [c10]Vadim Mottl, Sergey D. Dvoenko, Andrey Kopylov
:
Pattern Recognition in Interrelated Data: The Problem, Fundamental Assumptions, Recognition Algorithms. ICPR (1) 2004: 188-191 - 2002
- [c9]Vadim Mottl, Oleg Seredin, Sergey D. Dvoenko, Casimir A. Kulikowski, Ilya B. Muchnik:
Featureless Pattern Recognition in an Imaginary Hilbert Space. ICPR (2) 2002: 88-91 - [c8]Vadim Mottl, Alexey Kostin, Josef Kittler:
Support Object Classifiers with Rigid and Elastic Kernel Functions for Face Identification. ICPR (4) 2002: 205-208 - [c7]Vadim Mottl, Andrey Kopylov, Alexey Kostin, Alexey Yermakov, Josef Kittler:
Elastic Transformation of the Image Pixel Grid for Similarity Based Face Identification. ICPR (3) 2002: 549-552 - 2001
- [c6]Vadim Mottl, Sergey D. Dvoenko, Oleg Seredin
, Casimir A. Kulikowski, Ilya B. Muchnik:
Featureless Pattern Recognition in an Imaginary Hilbert Space and Its Application to Protein Fold Classification. MLDM 2001: 322-336 - 2000
- [c5]Vadim Mottl, Sergey D. Dvoenko, Vladimir Levyant, Ilya B. Muchnik:
Pattern Recognition in Spatial Data: A New Method of Seismic Explorations for Oil and Gas in Crystalline Basement Rocks. ICPR 2000: 2315-2318
1990 – 1999
- 1998
- [c4]Vadim Mottl, Alexander Blinov, Andrey Kopylov
, Alexey Kostin, Ilya B. Muchnik:
Variational methods in signal and image analysis. ICPR 1998: 525-527 - [c3]Vadim Mottl, Alexey Kostin, Andrey Kopylov:
Edge-preserving in generalized smoothing of signals and images. ICPR 1998: 1579-1581 - 1997
- [c2]Vadim Mottl, Alexander Blinov, Andrey Kopylov, Alexey Kostin:
Optimization Techniques on Pixel Neighborhood Graphs for Image Processing. GbRPR 1997: 135-145 - 1996
- [c1]Vadim Mottl, Ilya B. Muchnik, Alexander Blinov, Andrey Kopylov
:
Hidden tree-like quasi-Markov model and generalized technique for a class of image processing problems. ICPR 1996: 715-719
Coauthor Index
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