Asymptotically Optimal Sequential Change-Point Detection under Composite Hypotheses. - Boris Brodsky; Boris S. Darkhovsky (CDC/ECC, 2005)

Nonstationary nature of the brain activity as revealed by EEG/MEG: Methodological, practical and conceptual challenges. - Alexander Ya. Kaplan; Andrew A. Fingelkurts; Alexander A. Fingelkurts; Sergei V. Borisov; Boris S. Darkhovsky (Signal Process., 2005)

Stochastic recovery problem. - Boris S. Darkhovsky (Probl. Inf. Transm., 2008)

Non Asymptotic Minimax Estimation of Functionals with Noisy Observations. - Boris S. Darkhovskiy (Commun. Stat. Simul. Comput., 2012)

Epsilon-complexity of continuous functions - Boris S. Darkhovsky; Alexandra Piryatinska (CoRR, 2013)

Monte Carlo method of batch iterations: Probabilistic characteristics. - Boris S. Darkhovskiy; Yuri S. Popkov; Alexey Yu. Popkov (Autom. Remote. Control., 2015)

Iterative MC-algorithm to solve the global optimization problems. - Alexey Yu. Popkov; Boris S. Darkhovsky; Yuri S. Popkov (Autom. Remote. Control., 2017)

Binary classification of multichannel-EEG records based on the ϵ-complexity of continuous vector functions. - Alexandra Piryatinska; Boris S. Darkhovsky; Alexander Ya. Kaplan (Comput. Methods Programs Biomed., 2017)

A Method of Generating Random Vectors with a Given Probability Density Function. - Boris S. Darkhovsky; Yuri S. Popkov; Alexey Yu. Popkov; A. S. Aliev (Autom. Remote. Control., 2018)

Retrospective Change-Points Detection for Multidimensional Time Series of Arbitrary Nature: Model-Free Technology Based on the ϵ-Complexity Theory. - Alexandra Piryatinska; Boris S. Darkhovsky (Entropy, 2021)

Model-free classification of panel data via the ϵ-complexity theory. - Boris S. Darkhovsky; Alexandra Piryatinska (Commun. Stat. Simul. Comput., 2022)

Estimating the Hölder Exponents Based on the ε-Complexity of Continuous Functions: An Experimental Analysis of the Algorithm. - Yu. A. Dubnov; Alexey Y. Popkov; Boris S. Darkhovsky (Autom. Remote. Control., 2023)