Fedor Tsarev

发表

On NP-Hardness of the Paired de Bruijn Sound Cycle Problem pdf

Evgeny Kapun, Fedor Tsarev, 2013, WABI.

The use of evolutionary programming based on training examples for the generation of finite state machines for controlling objects with complex behavior

Anatoly Shalyto, A. V. Aleksandrov, Fedor Tsarev, 2013 .

APPLICATION OF GENETIC ALGORTIHMS FOR MOORE AUTOMATA AND SYSTEMS OF MEALY AUTOMATA CONSTRUCTION IN “ARTIFICIAL ANT” PROBLEM

Fedor Tsarev, Dmitry Sokolov, Andrey Davydov, 2017 .

GENOME CONTIGS ASSEMBLY METHOD BASED ON DE BRUJIN GRAPHS AND OVERLAP GRAPHS

Fedor Tsarev, Sergey Kazakov, Sergey Melnikov, 2018 .

ERRORS CORRECTION METHOD IN THE READINGS SET OF NUCLEOTIDE SEQUENCE

Shalyto Anatoly Abramovich, Fedor Tsarev, Sergey Kazakov, 2018 .

SCENARIO-BASED FINITE STATE MACHINE INDUCTION USING SAT-SOLVERS

Fedor Tsarev, Ulyantsev Vladimir Igorevich, 2018 .

Modeling Technology forOneClass ofMulti-Agent Systems withAutomata Based Programming

Anatoly Shalyto, Fedor Tsarev, Dmitry Paraschenko, 2006 .

Finite state machine induction using genetic algorithm based on testing and model checking

Fedor Tsarev, Kirill Egorov, 2011, GECCO '11.

Application of Genetic Programming for Generation of Controllers represented by Automata

Anatoly Shalyto, Fedor Tsarev, Dmitry Sokolov, 2009 .

Application of Genetic Algorithms for Construction of Moore Automaton and Systems of Interacting Mealy Automata in "Artificial Ant" Problem

Anatoly Shalyto, Fedor Tsarev, Dmitry Sokolov, 2008 .

De Bruijn Superwalk with Multiplicities Problem is NP-hard

Evgeny Kapun, Fedor Tsarev, 2013, BMC Bioinformatics.

Application of Genetic Algorithms for Construction of Moore Automaton and Systems of Interacting Mealy Automata in “Artificial Ant” Problem (Scientific advisor: prof. Anatoly A. Shalyto)

Anatoly Shalyto, Fedor Tsarev, Аndrey А. Davydov, 2008 .

Test-based extended finite-state machines induction with evolutionary algorithms and ant colony optimization

Daniil Chivilikhin, Vladimir Ulyantsev, Fedor Tsarev, 2012, GECCO '12.

Improving the quality of supervised finite-state machine construction using real-valued variables

Daniil Chivilikhin, Igor Buzhinsky, Vladimir Ulyantsev, 2014, GECCO.

Genetic algorithm for induction of finite automata with continuous and discrete output actions

Fedor Tsarev, Sergey Kazakov, Alexey A. Sergushichev, 2011, GECCO.

PROGRAMMING METHOD OF TOP-LEVEL FINITE AUTOMATA CREATION FOR THE UNMANNED AIRPLANE MODEL CONTROL BY TRAINING EXAMPLES

Shalyto Anatoly Abramovich, Fedor Tsarev, Sergey Kazakov, 2017 .

Combining De Bruijn Graphs, Overlap Graphs and Microassembly for De Novo Genome Assembly

Anatoly Shalyto, Fedor Tsarev, Alexey Sergushichev, 2013 .

APPLICATION OF GENETIC PROGRAMMING, FINITE STATE MACHINES AND NEURAL NETS FOR CONSTRUCTION OF CONTROL SYSTEM FOR UNNMANED AIRCRAFT

Fedor Tsarev, 2018 .

Search-based construction of finite-state machines with real-valued actions: new representation model

Igor Buzhinsky, Vladimir Ulyantsev, Anatoly Shalyto, 2013, GECCO '13 Companion.

APPLICATION OF GENETIC PROGRAMMING AND MODEL CHECKING FOR FINITE-STATE MACHINE INDUCTION ON THE BASE OF TESTS AND SPECIFICATION

Shalyto Anatoly Abramovich, Fedor Tsarev, Kirill Egorov, 2018 .

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

Inanç Birol, Dominique Lavenier, Hamidreza Chitsaz, 2013, GigaScience.

APPLICATION OF GENETIC PROGRAMMING AND OF REDUCED TRANSITION TABLES METHOD AND OF DECISION TREES METHOD FOR CONSTRUCTING A CONTROL SYSTEM FOR A MODEL OF AN UNMANNED AIRCRAFT

Fedor Tsarev, Dmitry Sokolov, Andrey Davydov, 2018 .

Extended Finite-State Machine Induction Using SAT-Solver

Vladimir Ulyantsev, Fedor Tsarev, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

Water pollution monitoring by an artificial sensory system performing in terms of Vibrio fischeri bacteria

Igor Buzhinsky, Fedor Tsarev, Andrey Legin, 2015 .