Inductive model generation and multimodel selection
Main publications:
Aduenko A.A., Motrenko A.P, Strijov V.V., “Object selection in credit scoring using covariance matrix of parameters estimations”, Annals of Operations Research, 260: 1–2 (2018), 3–21
Motrenko A.P, Strijov V.V., “Multi-way feature selection for ECoG-based Brain-Computer Interface”, Expert Systems with Applications, 114 (2018), 402-413
Katrutsa A., Strijov V.V., “Comprehensive study of feature selection methods to solve multicollinearity problem according to evaluation criteria”, Expert Systems with Applications, 76 (2017), 1-11
Kulunchakov A.S., Strijov V.V., “Generation of simple structured information retrieval functions by genetic algorithm without stagnation”, Expert Systems with Applications, 85 (2017), 221-230
Motrenko A.P, Strijov V.V., “Extracting Fundamental Periods to Segment Biomedical Signals”, IEEE Journal of Biomedical and Health Informatics, 20:6 (2016), 1466 - 1476
R. G. Neychev, I. A. Shibaev, V. V. Strijov, “Optimal spanning tree reconstruction in symbolic regression”, Inform. Primen., 17:1 (2023), 35–42
2022
2.
M. Gorpinich, O. Yu. Bakhteev, V. V. Strijov, “Gradient methods for optimizing metaparameters in the knowledge distillation problem”, Avtomat. i Telemekh., 2022, no. 10, 67–79; Autom. Remote Control, 83:10 (2022), 1544–1554
3.
A. I. Bazarova, A. V. Grabovoy, V. V. Strijov, “Analysis of the properties of probabilistic models in expert-augmented learning problems”, Avtomat. i Telemekh., 2022, no. 10, 47–59; Autom. Remote Control, 83:10 (2022), 1527–1537
4.
A. V. Grabovoy, V. V. Strijov, “Probabilistic interpretation of the distillation problem”, Avtomat. i Telemekh., 2022, no. 1, 150–168; Autom. Remote Control, 83:1 (2022), 123–137
A. M. Samokhina, R. G. Neychev, V. V. Goncharenko, R. K. Grigoryan, V. V. Strijov, “Classification models for P300 evoked potentials”, Sistemy i Sredstva Inform., 32:3 (2022), 36–49
2021
6.
A. V. Grabovoy, V. V. Strijov, “Bayesian distillation of deep learning models”, Avtomat. i Telemekh., 2021, no. 11, 16–29; Autom. Remote Control, 82:11 (2021), 1846–1856
O. S. Grebenkova, O. Yu. Bakhteev, V. V. Strijov, “Variational deep learning model optimization with complexity control”, Inform. Primen., 15:1 (2021), 42–49
8.
F. Yu. Yaushev, R. V. Isachenko, V. V. Strijov, “Concordant models for latent space projections in forecasting”, Sistemy i Sredstva Inform., 31:1 (2021), 4–16
9.
A. V. Grabovoy, V. V. Strijov, “Prior distribution selection for a mixture of experts”, Zh. Vychisl. Mat. Mat. Fiz., 61:7 (2021), 1149–1161; Comput. Math. Math. Phys., 61:7 (2021), 1140–1152
D. A. Anikeev, G. O. Penkin, V. V. Strijov, “Local approximation models for human physical activity classification”, Inform. Primen., 13:1 (2019), 40–48
15.
K. R. Usmanova, V. V. Strijov, “Models of detection relationship between time series in forecasting problems”, Sistemy i Sredstva Inform., 29:2 (2019), 12–30
2018
16.
O. Yu. Bakhteev, V. V. Strijov, “Deep learning model selection of suboptimal complexity”, Avtomat. i Telemekh., 2018, no. 8, 129–147; Autom. Remote Control, 79:8 (2018), 1474–1488
R. V. Isachenko, I. N. Zharikov, A. M. Bochkarev, V. V. Strijov, “Feature generation for physical activity classification”, Artificial Intelligence and Decision Making, 2018, no. 3, 20–27
19.
A. A. Aduenko, A. S. Vasileisky, E. A. Karatsuba, A. I. Karelov, I. A. Reyer, K. V. Rudakov, V. V. Strijov, “Detection of persistent scatterer pairs on satellite radar images with use of surface relief data”, Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2018, no. 2, 29–43
20.
K. R. Usmanova, S. P. Kudiyarov, R. V. Martyshkin, A. A. Zamkovoy, V. V. Strijov, “Analysis of relationships between indicators in forecasting cargo transportation”, Sistemy i Sredstva Inform., 28:3 (2018), 86–103
2017
21.
K. V. Rudakov, V. V. Strizhov, D. O. Kashirin, M. P. Kuznetsov, A. P. Motrenko, M. M. Stenina, “Selecting an optimal model for forecasting the volumes of railway goods transportation”, Avtomat. i Telemekh., 2017, no. 1, 91–105; Autom. Remote Control, 78:1 (2017), 75–87
I. O. Molybog, A. P. Motrenko, V. V. Strijov, “Improving classification quality for the task of finding intrinsic plagiarism”, Inform. Primen., 11:3 (2017), 60–72
23.
A. M. Bochkarev, I. L. Sofronov, V. V. Strijov, “Generation of expertly-interpreted models for prediction of core permeability”, Sistemy i Sredstva Inform., 27:3 (2017), 74–87
R. V. Isachenko, V. V. Strijov, “Metric learning in multiclass time series classification problem”, Inform. Primen., 10:2 (2016), 48–57
26.
A. V. Goncharov, V. V. Strijov, “Metric time series classification using weighted dynamic warping relative to centroids of classes”, Inform. Primen., 10:2 (2016), 36–47
27.
O. Yu. Bakhteev, M. S. Popova, V. V. Strijov, “Systems and means of deep learning for classification problems”, Sistemy i Sredstva Inform., 26:2 (2016), 4–22
2015
28.
A. A. Aduenko, A. S. Vasileisky, A. I. Karelov, I. A. Reyer, K. V. Rudakov, V. V. Strijov, “Algorithms of detection and registration of persistent scatterers in satellite radar images”, Computer Optics, 39:4 (2015), 622–630
K. V. Rudakov, L. N. Sanduleanu, A. A. Tokmakova, I. S. Yamschikov, I. A. Reyer, V. V. Strijov, “Terrain objects movement detection using SAR interferometry”, Computer Research and Modeling, 7:5 (2015), 1047–1060
M. M. Stenina, V. V. Strijov, “Forecasts reconciliation for hierarchical time series forecasting problem”, Inform. Primen., 9:2 (2015), 75–87
31.
M. Popova, V. Strijov, “Selection of optimal physical activity classification model using measurements of accelerometer”, Inform. Primen., 9:1 (2015), 76–86
A. V. Goncharov, M. S. Popova, V. V. Strijov, “Metric time series classification using dynamic warping relative to centroids of classes”, Sistemy i Sredstva Inform., 25:4 (2015), 52–64
M. S. Popova, V. V. Strijov, “Building superposition of deep learning neural networks for solving the problem of time series classification”, Sistemy i Sredstva Inform., 25:3 (2015), 60–77
R. K. Gazizullina, M. M. Stenina, V. V. Strijov, “Large capacity of railway cargo transportation forecasting”, Sistemy i Sredstva Inform., 25:1 (2015), 142–154
2014
35.
A. P. Motrenko, V. Strijov, “Obtaining an aggregated forecast of railway freight transportation using Kullback–Leibler distance”, Inform. Primen., 8:2 (2014), 86–97
36.
M. M. Stenina, V. V. Strijov, “Reconciliation of aggregated and disaggregated time series forecasts in nonparametric forecasting problems”, Sistemy i Sredstva Inform., 24:2 (2014), 23–36
G. I. Rudoy, V. V. Strijov, “Algorithms for inductive generation of superpositions for approximation of experimental data”, Inform. Primen., 7:1 (2013), 44–53
A. A. Tokmakova, V. Strijov, “Estimation of linear model hyperparameters for noise or correlated feature selection problem”, Inform. Primen., 6:4 (2012), 66–75
K. V. Vorontsov, A. N. Gromov, M. I. Zabezhailo, A. S. Inyakin, A. A. Lazarev, D. V. Lemtyuzhnikova, I. A. Sokolov, V. V. Strijov, Yul. V. Chekhovich, Yu. V. Chekhovich, “Foreword of the program committee of the conference “Mathematical pattern recognition methods””, Avtomat. i Telemekh., 2022, no. 10, 3–8; Autom. Remote Control, 83:10 (2022), 1491–1495
2021
41.
K. V. Vorontsov, Yu. I. Zhuravlev, A. A. Lazarev, D. V. Lemtyuzhnikova, K. V. Rudakov, V. V. Strijov, Yul. V. Chekhovich, Yu. V. Chekhovich, “Opening remarks by the Program Committee of the Conference “Intelligent Data Processing. Theory and Applications” (IDP-2020)”, Avtomat. i Telemekh., 2021, no. 10, 3–5; Autom. Remote Control, 82:10 (2021), 1633–1634
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