Lower Bounds for the Complexity of Learning Half-Spaces with Membership Queries. - Valery N. Shevchenko; Nikolai Yu. Zolotykh (ALT, 1998)

SVM Regression Parameters Optimization Using Parallel Global Search Algorithm. - Konstantin Barkalov; Alexey Polovinkin; Iosif B. Meyerov; Sergey V. Sidorov; Nikolai Yu. Zolotykh (PaCT, 2013)

The average cardinality of the minimal teaching set of a threshold function on a two-dimensional rectangular grid. - Max A. Alekseyev; Marina G. Basova; Nikolai Yu. Zolotykh (CoRR, 2013)

Alcuin's Propositiones de Civitatibus: the Earliest Packing Problems. - Nikolai Yu. Zolotykh (CoRR, 2013)

On the Minimal Teaching Sets of Two-Dimensional Threshold Functions. - Max A. Alekseyev; Marina G. Basova; Nikolai Yu. Zolotykh (SIAM J. Discret. Math., 2015)

On the Number of Irreducible Points in Polyhedra. - Aleksandr Yu. Chirkov; Nikolai Yu. Zolotykh (Graphs Comb., 2016)

SyntaxNet Errors from the Linguistic Point of View. - Oleg Durandin; Alexey Malafeev; Nikolai Yu. Zolotykh (AIST, 2017)

Specifying a positive threshold function via extremal points. - Vadim V. Lozin; Igor Razgon; Viktor Zamaraev; Elena Zamaraeva; Nikolai Yu. Zolotykh (ALT, 2017)

Linear read-once and related Boolean functions. - Vadim V. Lozin; Igor Razgon; Viktor Zamaraev; Elena Zamaraeva; Nikolai Yu. Zolotykh (Discret. Appl. Math., 2018)

Evolutionary Algorithms for Constructing an Ensemble of Decision Trees. - Evgeny Dolotov; Nikolai Yu. Zolotykh (AIST (Supplement), 2019)

On the Linear Separability of Random Points in the d-dimensional Spherical Layer and in the d-dimensional Cube. - Sergey V. Sidorov; Nikolai Yu. Zolotykh (IJCNN, 2019)

A Dynamic Algorithm for Constructing the Dual Representation of a Polyhedral Cone. - Sergey O. Semenov; Nikolai Yu. Zolotykh (MOTOR, 2019)

Educational Course "Introduction to Deep Learning Using the Intel neon Framework". - Valentina Kustikova; Nikolai Yu. Zolotykh; Maxim Zhiltsov (RuSCDays, 2019)

Two variations of graph test in double description method. - Nikolai Yu. Zolotykh; Sergei I. Bastrakov (Comput. Appl. Math., 2019)

Tuning hyperparameters of a SVM-based water demand forecasting system through parallel global optimization. - Antonio Candelieri; Ilaria Giordani; Francesco Archetti; Konstantin Barkalov; Iosif B. Meyerov; Alexey Polovinkin; Alexander Sysoyev; Nikolai Yu. Zolotykh (Comput. Oper. Res., 2019)

On the complexity of quasiconvex integer minimization problem. - Aleksandr Yu. Chirkov; Dmitry V. Gribanov; Dmitriy S. Malyshev; Panos M. Pardalos; Sergey I. Veselov; Nikolai Yu. Zolotykh (J. Glob. Optim., 2019)

Linear and Fisher Separability of Random Points in the d-dimensional Spherical Layer. - Sergey V. Sidorov; Nikolai Yu. Zolotykh (IJCNN, 2020)

LUDB: A New Open-Access Validation Tool for Electrocardiogram Delineation Algorithms. - Alena I. Kalyakulina; Igor I. Yusipov; Viktor A. Moskalenko; Alexander V. Nikolskiy; Konstantin A. Kosonogov; Grigory V. Osipov; Nikolai Yu. Zolotykh; Mikhail Ivanchenko (IEEE Access, 2020)

Deep Learning for ECG Segmentation. - Viktor A. Moskalenko; Nikolai Yu. Zolotykh; Grigory V. Osipov (CoRR, 2020)

Electrocardiogram Generation and Feature Extraction Using a Variational Autoencoder. - V. V. Kuznetsov; V. A. Moskalenko; Nikolai Yu. Zolotykh (CoRR, 2020)

On lattice point counting in Δ-modular polyhedra. - Dmitry V. Gribanov; Nikolai Yu. Zolotykh (CoRR, 2020)

A polynomial algorithm for minimizing discrete convic functions in fixed dimension. - Sergey I. Veselov; Dmitry V. Gribanov; Nikolai Yu. Zolotykh; Aleksandr Yu. Chirkov (Discret. Appl. Math., 2020)

Linear and Fisher Separability of Random Points in the d-Dimensional Spherical Layer and Inside the d-Dimensional Cube. - Sergey V. Sidorov; Nikolai Yu. Zolotykh (Entropy, 2020)

Accelerating Fourier-Motzkin elimination using bit pattern trees. - Sergey I. Bastrakov; Andrey Churkin; Nikolai Yu. Zolotykh (Optim. Methods Softw., 2021)

Rosenblatt's first theorem and frugality of deep learning. - A. N. Kirdin; Sergey V. Sidorov; Nikolai Yu. Zolotykh (CoRR, 2022)

Rosenblatt's First Theorem and Frugality of Deep Learning. - Alexander Kirdin; Sergey V. Sidorov; Nikolai Yu. Zolotykh (Entropy, 2022)

On Boolean threshold functions with minimum specification number. - Vadim V. Lozin; Viktor Zamaraev; Elena Zamaraeva; Nikolai Yu. Zolotykh (Inf. Comput., 2022)

On lattice point counting in $ varDelta $-modular polyhedra. - Dmitry V. Gribanov; Nikolai Yu. Zolotykh (Optim. Lett., 2022)

How to find the convex hull of all integer points in a polyhedron? - Sergey O. Semenov; Nikolai Yu. Zolotykh (Optim. Lett., 2022)

Faster Integer Points Counting in Parametric Polyhedra. - Dmitry V. Gribanov; Dmitriy S. Malyshev; Panos M. Pardalos; Nikolai Yu. Zolotykh (CoRR, 2023)

Faster algorithms for sparse ILP and hypergraph multi-packing/multi-cover problems. - Dmitry V. Gribanov; Ivan A. Shumilov; Dmitry S. Malyshev; Nikolai Yu. Zolotykh (J. Glob. Optim., 2024)