Regression trees for analysis of mutational spectra in nucleotide sequences. - Vladimir B. Berikov; Igor B. Rogozin (Bioinform., 1999)

An approach to the evaluation of the performance of a discrete classifier. - Vladimir B. Berikov (Pattern Recognit. Lett., 2002)

The influence of prior knowledge on the expected performance of a classifier. - Vladimir B. Berikov; Alexander Litvinenko (Pattern Recognit. Lett., 2003)

Construction of an Event Tree on the Basis of Expert Knowledge and Time Series. - Gennady Lbov; Vladimir B. Berikov (KONT/KPP, 2007)

Bayesian Model of Recognition on a Finite Set of Events. - Vladimir B. Berikov; Gennady Lbov (SETN, 2008)

Construction of the Ensemble of Logical Models in Cluster Analysis. - Vladimir B. Berikov (ICIC (2), 2009)

A Latent Variable Pairwise Classification Model of a Clustering Ensemble. - Vladimir B. Berikov (MCS, 2011)

Weighted ensemble of algorithms for complex data clustering. - Vladimir B. Berikov (Pattern Recognit. Lett., 2014)

Cluster Ensemble with Averaged Co-Association Matrix Maximizing the Expected Margin. - Vladimir B. Berikov (DOOR (Supplement), 2016)

Ensemble clustering based on weighted co-association matrices: Error bound and convergence properties. - Vladimir B. Berikov; Igor Pestunov (Pattern Recognit., 2017)

Regression Analysis with Cluster Ensemble and Kernel Function. - Vladimir B. Berikov; Taisiya Vinogradova (AIST, 2018)

Semi-supervised Classification Using Multiple Clustering and Low-Rank Matrix Operations. - Vladimir B. Berikov (MOTOR, 2019)

Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix Decomposition under Uncertainties. - Vladimir B. Berikov; Alexander Litvinenko (CoRR, 2019)

Recognition of Tomographic Images in the Diagnosis of Stroke. - Kirill Kalmutskiy; Andrey Tulupov; Vladimir B. Berikov (ICPR Workshops (5), 2020)

Heterogeneous Transfer Learning in Ensemble Clustering. - Vladimir B. Berikov (CoRR, 2020)

On a Weakly Supervised Classification Problem. - Vladimir B. Berikov; Alexander Litvinenko; Igor Pestunov; Yuriy Sinyavskiy (AIST, 2021)

Weakly Supervised Regression Using Manifold Regularization and Low-Rank Matrix Representation. - Vladimir B. Berikov; Alexander Litvinenko (MOTOR, 2021)

Solving weakly supervised regression problem using low-rank manifold regularization. - Vladimir B. Berikov; Alexander Litvinenko (CoRR, 2021)

Identification of unknown parameters and prediction with hierarchical matrices. - Alexander Litvinenko; Ronald Kriemann; Vladimir B. Berikov (CoRR, 2021)

Weakly supervised semantic segmentation of tomographic images in the diagnosis of stroke. - Anna Dobshik; Andrey Tulupov; Vladimir B. Berikov (CoRR, 2021)

ERANNs: Efficient residual audio neural networks for audio pattern recognition. - Sergey Verbitskiy; Vladimir B. Berikov; Viacheslav Vyshegorodtsev (Pattern Recognit. Lett., 2022)

Model and Method for Constructing a Heterogeneous Cluster Ensemble. - Vladimir B. Berikov (Autom. Remote. Control., 2022)

Ensemble Clustering with Heterogeneous Transfer Learning. - Vladimir B. Berikov (AIST, 2023)

Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks. - A. V. Dobshik; S. K. Verbitskiy; I. A. Pestunov; K. M. Sherman; Yu. N. Sinyavskiy; A. A. Tulupov; Vladimir B. Berikov (CoRR, 2023)

A fast consistent grid-based clustering algorithm. - Anton S. Tarasenko; Vladimir B. Berikov; Igor Pestunov; Sergey V. Ablameyko 001; Pavel S. Ruzankin (Pattern Anal. Appl., 2024)