Vadim Mottl

发表

Supervised Selective Combining Pattern Recognition Modalities and Its Application to Signature Verification by Fusing On-Line and Off-Line Kernels

David Windridge, Alexander Tatarchuk, Valentina Sulimova, 2009, MCS.

Elastic transformation of the image pixel grid for similarity based face identification

Josef Kittler, Vadim Mottl, Andrey Kopylov, 2002, Object recognition supported by user interaction for service robots.

A Bayesian Approach to Sparse Cox Regression in High-Dimentional Survival Analysis

Vadim Mottl, Olga Krasotkina, V. Mottl, 2015, MLDM.

Bayesian Estimation of Time-Varying Regression with Changing Time-Volatility for Detection of Hidden Events in Non-Stationary Signals

Vadim Mottl, Andrey Kopylov, Olga Krasotkina, 2010 .

Featureless pattern recognition in an imaginary Hilbert space

Casimir A. Kulikowski, Vadim Mottl, Ilya B. Muchnik, 2002, Object recognition supported by user interaction for service robots.

Recognition of Herpes Viruses on the Basis of a New Metric for Protein Sequences

Valentina Sulimova, Vadim Mottl, Oleg Seredin, 2019 .

Quick breast cancer detection via classification of evoked EEG potentials in the mammologist's brain

David Windridge, Valentina Sulimova, Vadim Mottl, 2019, 2019 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON).

Compactness Hypothesis, Potential Functions, and Rectifying Linear Space in Machine Learning

Vadim Mottl, Oleg Seredin, Olga Krasotkina, 2017, Braverman Readings in Machine Learning.

Adaptive nonstationary regression analysis

Vadim Mottl, Olga Krasotkina, 2008, 2008 19th International Conference on Pattern Recognition.

An Automatic Matching Procedure of Ultrasonic Railway Defectograms

Valentina Sulimova, Vadim Mottl, Anton Malenichev, 2014, MLDM.

A Modified Neutral Point Method for Kernel-Based Fusion of Pattern-Recognition Modalities with Incomplete Data Sets

David Windridge, Alexander Tatarchuk, Vadim Mottl, 2011, MCS.

Pattern recognition in spatial data: a new method of seismic explorations for oil and gas in crystalline basement rocks

Vadim Mottl, Ilya B. Muchnik, Sergey Dvoenko, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Variational methods in signal and image analysis

Vadim Mottl, Andrey Kopylov, Alexey Kostin, 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

Recognition of Herpes Viruses on the Basis of a New Metric for Protein Sequences

Valentina Sulimova, Vadim Mottl, Oleg Seredin, 2016, IDP.

Bayesian Approach to the Pattern Recognition Problem in Nonstationary Environment

Vadim Mottl, Olga Krasotkina, Pavel A. Turkov, 2011, PReMI.

A Bayesian Approach to Sparse Learning-to-Rank for Search Engine Optimization

Vadim Mottl, Olga Krasotkina, V. Mottl, 2015, MLDM.

Selection of Subsets of Ordered Features in Machine Learning

Vadim Mottl, Andrey Kopylov, Oleg Seredin, 2009, Trans. Mach. Learn. Data Min..

Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion

Alexander Tatarchuk, Valentina Sulimova, Vadim Mottl, 2007, MCS.

Sparse logistic regression with supervised selectivity for predictors selection in credit scoring

Vadim Mottl, Olga Krasotkina, Zhosan Yulia, 2016, SoICT.

Sparse Multimodal Classification of EEG Signals from Rapid Serial Visual Presentation of Diagnostic Images

David Windridge, Valentina Sulimova, Vadim Mottl, 2019, IAPR International Conference on Machine Learning and Data Mining in Pattern Recognition.

The Neutral Point Method for Kernel-Based Combination of Disjoint Training Data in Multi-modal Pattern Recognition

David Windridge, Alexander Tatarchuk, Vadim Mottl, 2007, MCS.

Linear complexity algorithms for high dimensional SVM and regression problems with smart sparse regularization

Alexander Tatarchuk, Valentina Sulimova, Vadim Mottl, 2019, MLDM.

Computational Complexity of Dependence Estimation via Generalized Linear Models in Multidimensional Feature Spaces

Valentina Sulimova, Vadim Mottl, Olga Krasotkina, 2019, 2019 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON).

The Bayesian logistic regression in pattern recognition problems under concept drift

Vadim Mottl, Olga Krasotkina, Pavel A. Turkov, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Application of the Multi-modal Relevance Vector Machine to the Problem of Protein Secondary Structure Prediction

David Windridge, Valentina Sulimova, Vadim Mottl, 2012, PRIB.

Feature Selection for Handling Concept Drift in the Data Stream Classification

Vadim Mottl, Olga Krasotkina, Alexey Sychugov, 2016, MLDM.

Methods of Hyperparameter Estimation in Time-Varying Regression Models with Application to Dynamic Style Analysis of Investment Portfolios

Vadim Mottl, Olga Krasotkina, Michael Markov, 2017, MLDM.

A Maximum-Likelihood Formulation and EM Algorithm for the Protein Multiple Alignment Problem

Casimir A. Kulikowski, Valentina Sulimova, Vadim Mottl, 2010, PRIB.

Signature verification based on fusion of on-line and off-line kernels

Valentina Sulimova, Vadim Mottl, Mikhail Lange, 2008, 2008 19th International Conference on Pattern Recognition.

A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities

David Windridge, Alexander Tatarchuk, Vadim Mottl, 2010, MCS.

Finding the Largest Hypercavity in a Linear Data Space

Valentina Sulimova, Vadim Mottl, Oleg Seredin, 2014, 2014 22nd International Conference on Pattern Recognition.

Constrained Regularized Regression Model Search in Large Sets of Regressors

Vadim Mottl, Alexey Morozov, Olga Krasotkina, 2018, MLDM.

Principles of Multi-kernel Data Mining

Vadim Mottl, Ilya B. Muchnik, Oleg Seredin, 2005, MLDM.

Handling Multimodal Information Fusion with Missing Observations Using the Neutral Point Substitution Method

David Windridge, Norman Poh, Alexander Tatarchuk, 2009, MCS.

Hidden tree-like quasi-Markov model and generalized technique for a class of image processing problems

Vadim Mottl, Andrey Kopylov, Ilya B. Muchnik, 1996, Proceedings of 13th International Conference on Pattern Recognition.

A Class of Evolution-Based Kernels for Protein Homology Analysis: A Generalization of the PAM Model

Casimir A. Kulikowski, Valentina Sulimova, Vadim Mottl, 2009, ISBRA.

Automatic Rail Flaw Localization and Recognition by Featureless Ultrasound Signal Analysis

Valentina Sulimova, Vadim Mottl, Olga Krasotkina, 2018, MLDM.

A Signal Processing Algorithm Based on Parametric Dynamic Programming

Vadim Mottl, Andrey Kopylov, Olga Krasotkina, 2010, ICISP.

Support object classifiers with rigid and elastic kernel functions for face identification

Josef Kittler, Vadim Mottl, Alexey Kostin, 2002, Object recognition supported by user interaction for service robots.

Dynamic Programming for Bayesian Logistic Regression Learning under Concept Drift

Vadim Mottl, Olga Krasotkina, Pavel A. Turkov, 2013, PReMI.

Pattern recognition in interrelated data: the problem, fundamental assumptions, recognition algorithms

Vadim Mottl, Andrey Kopylov, Sergey Dvoenko, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Supervised Selective Combination of Diverse Object-Representation Modalities for Regression Estimation

Vadim Mottl, Oleg Seredin, Olga Krasotkina, 2015, MCS.

Featureless Pattern Recognition in an Imaginary Hilbert Space and Its Application to Protein Fold Classification

Casimir A. Kulikowski, Vadim Mottl, Ilya B. Muchnik, 2001, MLDM.

Linear Regression via Elastic Net: Non-enumerative Leave-One-Out Verification of Feature Selection

David Windridge, Vadim Mottl, Olga Krasotkina, 2014 .

Bayesian Approach to the Concept Drift in the Pattern Recognition Problems

Vadim Mottl, Olga Krasotkina, Pavel A. Turkov, 2012, MLDM.

Non-enumerative Cross Validation for the Determination of Structural Parameters in Feature-Selective SVMs

David Windridge, Alexander Tatarchuk, Vadim Mottl, 2014, 2014 22nd International Conference on Pattern Recognition.

Quasi-statistical approach to the problem of stereo-image matching

Sergey Yu. Zheltov, Vadim Mottl, Andrey Kopylov, 1995, Other Conferences.

Multi-class Classification in Big Data

Vadim Mottl, Oleg Seredin, Anton Malenichev, 2016, AIST.

Supervised Selective Kernel Fusion for Membrane Protein Prediction

David Windridge, Alexander Tatarchuk, Valentina Sulimova, 2014, PRIB.

Potential Functions for Signals and Symbolic Sequences

Valentina Sulimova, Vadim Mottl, 2017, Braverman Readings in Machine Learning.

Addressing Missing Values in Kernel-Based Multimodal Biometric Fusion Using Neutral Point Substitution

David Windridge, Norman Poh, Alexander Tatarchuk, 2010, IEEE Transactions on Information Forensics and Security.

Selectivity supervision in combining pattern-recognition modalities by feature- and kernel-selective support vector machines

David Windridge, Alexander Tatarchuk, Vadim Mottl, 2008, 2008 19th International Conference on Pattern Recognition.

Optimization Techniques on Pixel Neighborhood Graphs for Image Processing

Vadim Mottl, Andrey Kopylov, Alexey Kostin, 1997, GbRPR.

Convex support and Relevance Vector Machines for selective multimodal pattern recognition

David Windridge, Alexander Tatarchuk, Vadim Mottl, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Bellman Functions on Trees for Segmentation, Generalized Smoothing, Matching and Multi-Alignment in

Vadim Mottl, Ilya Muchnik, 1998 .

Bellman Functions on Trees for Segmentation, Generalized Smoothing, Matching Multi-Alignment in Massive Data Sets

Vadim Mottl, Ilya Muchnik, 1998 .