Bogdan Grechuk

According to our database, Bogdan Grechuk authored at least 27 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Benchmark-based deviation and drawdown measures in portfolio optimization.

Michael Zabarankin, Bogdan Grechuk, Dawei Hao

Optim. Lett., September, 2024

Buffered and Reduced Multidimensional Distribution Functions and Their Application in Optimization.

Bogdan Grechuk, Michael Zabarankin, Alexander Mafusalov, Stan Uryasev

Optim. Lett., March, 2024

2023

Extended gradient of convex function and capital allocation.

Bogdan Grechuk

Eur. J. Oper. Res., 2023

2022

On the smallest open Diophantine equations.

Bogdan Grechuk

SIGACT News, 2022

Individual and cooperative portfolio optimization as linear program.

Bogdan Grechuk, Dawei Hao

Optim. Lett., 2022

2021

General stochastic separation theorems with optimal bounds.

Bogdan Grechuk, Alexander N. Gorban, Ivan Yu. Tyukin

Neural Networks, 2021

High-Dimensional Separability for One- and Few-Shot Learning.

Alexander N. Gorban, Bogdan Grechuk, Evgeny M. Mirkes, Sergey V. Stasenko, Ivan Yu. Tyukin

Entropy, 2021

2020

Matrix Difference Equations in Applied Mathematics.

Michael Zabarankin, Bogdan Grechuk

SIAM J. Appl. Math., 2020

A Convex Cover for Closed Unit Curves has Area at Least 0.0975.

Bogdan Grechuk, Sittichoke Som-Am

Int. J. Comput. Geom. Appl., 2020

A convex cover for closed unit curves has area at least 0.1.

Bogdan Grechuk, Sittichoke Som-Am

Discret. Optim., 2020

2019

Regression analysis: likelihood, error and entropy.

Bogdan Grechuk, Michael Zabarankin

Math. Program., 2019

Kernel Stochastic Separation Theorems and Separability Characterizations of Kernel Classifiers.

Ivan Yu. Tyukin, Alexander N. Gorban, Bogdan Grechuk, Stephen Green

Proceedings of the International Joint Conference on Neural Networks, 2019

Practical stochastic separation theorems for product distributions.

Bogdan Grechuk

Proceedings of the International Joint Conference on Neural Networks, 2019

2018

Correction of AI systems by linear discriminants: Probabilistic foundations.

Alexander N. Gorban, A. Golubkov, Bogdan Grechuk, Eugenij Moiseevich Mirkes, Ivan Tyukin

Inf. Sci., 2018

Direct data-based decision making under uncertainty.

Bogdan Grechuk, Michael Zabarankin

Eur. J. Oper. Res., 2018

Augmented Artificial Intelligence: a Conceptual Framework.

Alexander N. Gorban, Bogdan Grechuk, Ivan Yu. Tyukin

CoRR, 2018

2017

Sensitivity Analysis in Applications with Deviation, Risk, Regret, and Error Measures.

Bogdan Grechuk, Michael Zabarankin

SIAM J. Optim., 2017

Forward and Inverse Problems in Two-Phase Fluid Dynamics.

Michael Zabarankin, Bogdan Grechuk

SIAM J. Control. Optim., 2017

Synergy effect of cooperative investment.

Bogdan Grechuk, Michael Zabarankin

Ann. Oper. Res., 2017

2016

Inverse portfolio problem with coherent risk measures.

Bogdan Grechuk, Michael Zabarankin

Eur. J. Oper. Res., 2016

2015

The center of a convex set and capital allocation.

Bogdan Grechuk

Eur. J. Oper. Res., 2015

2014

A simple SSD-efficiency test.

Bogdan Grechuk

Optim. Lett., 2014

Risk averse decision making under catastrophic risk.

Bogdan Grechuk, Michael Zabarankin

Eur. J. Oper. Res., 2014

Inverse portfolio problem with mean-deviation model.

Bogdan Grechuk, Michael Zabarankin

Eur. J. Oper. Res., 2014

2012

Optimal risk sharing with general deviation measures.

Bogdan Grechuk, Michael Zabarankin

Ann. Oper. Res., 2012

2011

Lower Semicontinuous Functions.

Bogdan Grechuk

Arch. Formal Proofs, 2011

2009

Maximum Entropy Principle with General Deviation Measures.

Bogdan Grechuk, Anton Molyboha, Michael Zabarankin

Math. Oper. Res., 2009