Attributive and Object Subcontexts in Inferring Good Maximally Redundant Tests. - Xenia A. Naidenova; Vladimir Parkhomenko (CLA, 2014)

Context-Dependent Deductive and Inductive Reasoning Based on Good Diagnostic Tests. - Xenia A. Naidenova; Vladimir Parkhomenko (FCA&A@ICFCA, 2015)

Modification of Good Tests in Dynamic Contexts: Application to Modeling Intellectual Development of Cadets. - Xenia A. Naidenova; Vladimir Parkhomenko; Konstantin Shvetsov; Vladislav Yusupov; Raisa Kuzina (SCAKD@CLA, 2016)

Two Prediction Models for Some Economic Indicators of the Russian Arctic Zone. - Sergey A. Chernogorskiy; Konstantin Shvetsov; Vladimir Parkhomenko (IntelliSys (1), 2016)

Granular Computing and Incremental Classification. - Xenia A. Naidenova; Vladimir Parkhomenko (FCA4AI@ECAI, 2020)

Contribution to attributive and object subcontexts in inferring good maximally redundant tests. - Xenia A. Naidenova; Vladimir Parkhomenko (Discret. Appl. Math., 2020)

Nerual Network System For Ground Robot Path Planning and Obstacle Avoidance. - Vladimir Parkhomenko; Mikhail Yu. Medvedev (ICMRE, 2021)

A Concept of Self-Supervised Logical Rule Inference in Symbolic Classifications. - Xenia A. Naidenova; Vladimir Parkhomenko (FCA4AI@IJCAI, 2021)

Plausible Reasoning in an Algorithm for Generation of Good Classification Tests. - Xenia A. Naidenova; Vladimir Parkhomenko; Taniana A. Martirova; A. V. Schukin (Autom. Remote. Control., 2024)