Lev V. Utkin

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 83

Top Venues

Publications

Andrei V. Konstantinov, Stanislav R. Kirpichenko, Lev V. Utkin
Generating Survival Interpretable Trajectories and Data. CoRR (2024)
Stanislav Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov, Vladimir Muliukha
BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect. Algorithms 17 (1) (2024)
Rinat I. Dumaev, Sergei A. Molodyakov, Lev V. Utkin
Concept-based Explainable Malignancy Scoring on Pulmonary Nodules in CT Images. CoRR (2024)
Andrei V. Konstantinov, Lev V. Utkin
Incorporating Expert Rules into Neural Networks in the Framework of Concept-Based Learning. CoRR (2024)
Lev V. Utkin, Andrei V. Konstantinov, Stanislav R. Kirpichenko
FI-CBL: A Probabilistic Method for Concept-Based Learning with Expert Rules. CoRR (2024)
Andrei V. Konstantinov, Boris V. Kozlov, Stanislav R. Kirpichenko, Lev V. Utkin
Dual feature-based and example-based explanation methods. CoRR (2024)
Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha, Vladimir S. Zaborovsky
GBMILs: Gradient Boosting Models for Multiple Instance Learning. ICR (2023)
Andrei V. Konstantinov, Lev V. Utkin
Attention-like feature explanation for tabular data. Int. J. Data Sci. Anal. 16 (1) (2023)
Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov
SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator. CoRR (2023)
Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha
Multiple Instance Learning with Trainable Soft Decision Tree Ensembles. Algorithms 16 (8) (2023)
Andrei V. Konstantinov, Stanislav Kirpichenko, Lev V. Utkin
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression. Algorithms 16 (5) (2023)
Andrei V. Konstantinov, Lev V. Utkin, Alexey Lukashin, Vladimir Muliukha
Neural Attention Forests: Transformer-Based Forest Improvement. CoRR (2023)
Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha
LARF: Two-Level Attention-Based Random Forests with a Mixture of Contamination Models. Informatics 10 (2) (2023)
Andrei V. Konstantinov, Lev V. Utkin
Interpretable ensembles of hyper-rectangles as base models. Neural Comput. Appl. 35 (29) (2023)
Andrei V. Konstantinov, Lev V. Utkin
Interpretable Ensembles of Hyper-Rectangles as Base Models. CoRR (2023)
Andrei V. Konstantinov, Lev V. Utkin
A New Computationally Simple Approach for Implementing Neural Networks with Output Hard Constraints. CoRR (2023)
Andrei V. Konstantinov, Lev V. Utkin
Multiple Instance Learning with Trainable Decision Tree Ensembles. CoRR (2023)
Lev V. Utkin, Andrei V. Konstantinov, Stanislav R. Kirpichenko
Attention and self-attention in random forests. Prog. Artif. Intell. 12 (3) (2023)
Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov
SurvBeNIM: The Beran-Based Neural Importance Model for Explaining the Survival Models. CoRR (2023)
Lev V. Utkin, Andrey Y. Ageev, Andrei V. Konstantinov, Vladimir Muliukha
Improved Anomaly Detection by Using the Attention-Based Isolation Forest. Algorithms 16 (1) (2023)
Lev V. Utkin, Egor D. Satyukov, Andrei V. Konstantinov
SurvNAM: The machine learning survival model explanation. Neural Networks 147 (2022)
Andrei V. Konstantinov, Lev V. Utkin, Stanislav Kirpichenko
AGBoost: Attention-based Modification of Gradient Boosting Machine. FRUCT (2022)
Lev V. Utkin, Andrei V. Konstantinov
Attention and Self-Attention in Random Forests. CoRR (2022)
Andrei V. Konstantinov, Lev V. Utkin
Multiple Instance Learning through Explanation by Using a Histopathology Example. FRUCT (2022)
Andrei V. Konstantinov, Lev V. Utkin
LARF: Two-level Attention-based Random Forests with a Mixture of Contamination Models. CoRR (2022)
Lev V. Utkin, Andrei V. Konstantinov
Attention-based random forest and contamination model. Neural Networks 154 (2022)
Andrei V. Konstantinov, Lev V. Utkin
Multi-attention multiple instance learning. Neural Comput. Appl. 34 (16) (2022)
Andrei V. Konstantinov, Lev V. Utkin, Stanislav Kirpichenko
AGBoost: Attention-based Modification of Gradient Boosting Machine. CoRR (2022)
Andrei V. Konstantinov, Stanislav R. Kirpichenko, Lev V. Utkin
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression. CoRR (2022)
Lev V. Utkin, Andrei V. Konstantinov
Ensembles of Random SHAPs. Algorithms 15 (11) (2022)
Lev V. Utkin, Andrei V. Konstantinov
Attention-based Random Forest and Contamination Model. CoRR (2022)
Stanislav R. Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov
BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect. CoRR (2022)
Lev V. Utkin, Andrey Y. Ageev, Andrei V. Konstantinov
Improved Anomaly Detection by Using the Attention-Based Isolation Forest. CoRR (2022)
Lev V. Utkin, Vladimir S. Zaborovsky, Maxim S. Kovalev, Andrei V. Konstantinov, Natalia A. Politaeva, Alexey Lukashin
Uncertainty Interpretation of the Machine Learning Survival Model Predictions. IEEE Access 9 (2021)
Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha
Gradient Boosting Machine with Partially Randomized Decision Trees. FRUCT (2021)
Lev V. Utkin, Egor D. Satyukov, Andrei V. Konstantinov
SurvNAM: The machine learning survival model explanation. CoRR (2021)
Lev V. Utkin, Pavel D. Drobintsev, Maxim Kovalev, Andrei V. Konstantinov
Combining an Autoencoder and a Variational Autoencoder for Explaining the Machine Learning Model Predictions. FRUCT (2021)
Lev V. Utkin, Andrei V. Konstantinov, Kirill A. Vishniakov
An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data. CoRR (2021)
Andrei V. Konstantinov, Lev V. Utkin
Interpretable machine learning with an ensemble of gradient boosting machines. Knowl. Based Syst. 222 (2021)
Maxim Kovalev, Lev V. Utkin, Frank P. A. Coolen, Andrei V. Konstantinov
Counterfactual Explanation of Machine Learning Survival Models. Informatica 32 (4) (2021)
Andrei V. Konstantinov, Lev V. Utkin
Multi-Attention Multiple Instance Learning. CoRR (2021)
Andrei V. Konstantinov, Lev V. Utkin
Attention-like feature explanation for tabular data. CoRR (2021)
Lev V. Utkin, Andrei V. Konstantinov
Ensembles of Random SHAPs. CoRR (2021)
Anna A. Meldo, Lev V. Utkin, Maxim Kovalev, Ernest M. Kasimov
The natural language explanation algorithms for the lung cancer computer-aided diagnosis system. Artif. Intell. Medicine 108 (2020)
Lev V. Utkin
An imprecise deep forest for classification. Expert Syst. Appl. 141 (2020)
Andrei V. Konstantinov, Lev V. Utkin
Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines. CoRR (2020)
Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov
SurvLIME-Inf: A simplified modification of SurvLIME for explanation of machine learning survival models. CoRR (2020)
Vladimir Muliukha, Alexey Lukashin, Lev V. Utkin, Mikhail Popov, Anna A. Meldo
Anomaly Detection Approach in Cyber Security for User and Entity Behavior Analytics System. ESANN (2020)
Maxim S. Kovalev, Lev V. Utkin
A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds. Neural Networks 132 (2020)
Maxim S. Kovalev, Lev V. Utkin, Ernest M. Kasimov
SurvLIME: A method for explaining machine learning survival models. CoRR (2020)
Lev V. Utkin, Kirill D. Zhuk
Improvement of the Deep Forest Classifier by a Set of Neural Networks. Informatica (Slovenia) 44 (1) (2020)
Maxim S. Kovalev, Lev V. Utkin
Counterfactual explanation of machine learning survival models. CoRR (2020)
Lev V. Utkin, Maxim Kovalev, Ernest M. Kasimov
Explanation of Siamese Neural Networks for Weakly Supervised Learning. Comput. Informatics 39 (6) (2020)
Lev V. Utkin, Maxim S. Kovalev, Frank P. A. Coolen
Imprecise weighted extensions of random forests for classification and regression. Appl. Soft Comput. 92 (2020)
Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Anna A. Meldo
A New Adaptive Weighted Deep Forest and Its Modifications. Int. J. Inf. Technol. Decis. Mak. 19 (4) (2020)
Andrei V. Konstantinov, Lev V. Utkin
Gradient boosting machine with partially randomized decision trees. CoRR (2020)
Maxim S. Kovalev, Lev V. Utkin, Ernest M. Kasimov
SurvLIME: A method for explaining machine learning survival models. Knowl. Based Syst. 203 (2020)
Maxim S. Kovalev, Lev V. Utkin
A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds. CoRR (2020)
Lev V. Utkin, Mikhail V. Kots, Viacheslav S. Chukanov, Andrei V. Konstantinov, Anna A. Meldo
Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors. Int. J. Artif. Intell. Tools 29 (5) (2020)
Andrei V. Konstantinov, Lev V. Utkin
A Generalized Stacking for Implementing Ensembles of Gradient Boosting Machines. CoRR (2020)
Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Anna A. Meldo
An Adaptive Weighted Deep Forest Classifier. CoRR (2019)
Lev V. Utkin
An imprecise extension of SVM-based machine learning models. Neurocomputing 331 (2019)
Anna A. Meldo, Lev V. Utkin, Alexey Lukashin, Vladimir Muliukha, Vladimir S. Zaborovsky
Database Acquisition for the Lung Cancer Computer Aided Diagnostic Systems. FRUCT (2019)
Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov
An explanation method for Siamese neural networks. CoRR (2019)
Lev V. Utkin, Maxim Kovalev, Anna A. Meldo, Frank P. A. Coolen
Imprecise Extensions of Random Forests and Random Survival Forests. ISIPTA (2019)
Lev V. Utkin, Maxim Kovalev, Anna A. Meldo
A deep forest classifier with weights of class probability distribution subsets. Knowl. Based Syst. 173 (2019)
Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Mikhail A. Ryabinin, Anna A. Meldo
A weighted random survival forest. Knowl. Based Syst. 177 (2019)
Lev V. Utkin, Andrei V. Konstantinov, Anna A. Meldo, Mikhail A. Ryabinin, Viacheslav S. Chukanov
A Deep Forest Improvement by Using Weighted Schemes. FRUCT (2019)
Lev V. Utkin, Mikhail A. Ryabinin
Discriminative Metric Learning with Deep Forest. Int. J. Artif. Intell. Tools 28 (2) (2019)
Lev V. Utkin, Mikhail V. Kots, Viacheslav S. Chukanov
Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors. CoRR (2019)
Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Mikhail A. Ryabinin, Anna A. Meldo
A weighted random survival forest. CoRR (2019)
Lev V. Utkin, Anna A. Meldo, Maxim Kovalev, Ernest M. Kasimov
An Ensemble of Triplet Neural Networks for Differential Diagnostics of Lung Cancer. FRUCT (2019)
Lev V. Utkin, Frank P. A. Coolen
A robust weighted SVR-based software reliability growth model. Reliab. Eng. Syst. Saf. 176 (2018)
Lev V. Utkin, Mikhail A. Ryabinin
A Siamese Deep Forest. Knowl. Based Syst. 139 (2018)
Lev V. Utkin, Yulia A. Zhuk
A modification of the Lasso method by using the Bahadur representation for the genome-wide association study. Informatica (Slovenia) 42 (2) (2018)
Sergey V. Gurov, Lev V. Utkin
Reliability of repairable reserved systems with failure aftereffect. Autom. Remote. Control. 78 (1) (2017)
Lev V. Utkin, Vladimir S. Zaborovsky, Sergey G. Popov
Siamese neural network for intelligent information security control in multi-robot systems. Autom. Control. Comput. Sci. 51 (8) (2017)
Lev V. Utkin, Mikhail A. Ryabinin
A Siamese Deep Forest. CoRR (2017)
Lev V. Utkin, Mikhail A. Ryabinin
Discriminative Metric Learning with Deep Forest. CoRR (2017)
Lev V. Utkin, Yulia A. Zhuk
An one-class classification support vector machine model by interval-valued training data. Knowl. Based Syst. 120 (2017)
Lev V. Utkin, Yulia A. Zhuk
Interval SVM-Based Classification Algorithm Using the Uncertainty Trick. Int. J. Artif. Intell. Tools 26 (4) (2017)
Lev V. Utkin, V. S. Zaborovskii, Sergey G. Popov
Detection of anomalous behavior in a robot system based on deep learning elements. Autom. Control. Comput. Sci. 50 (8) (2016)
Lev V. Utkin, Anatoly I. Chekh, Yulia A. Zhuk
Binary classification SVM-based algorithms with interval-valued training data using triangular and Epanechnikov kernels. Neural Networks 80 (2016)
Lev V. Utkin, Yulia A. Zhuk
Robust Classifiers Using Imprecise Probability Models and Importance of Classes. Int. J. Artif. Intell. Tools 24 (1) (2015)
Lev V. Utkin, Anatoly I. Chekh
A new robust model of one-class classification by interval-valued training data using the triangular kernel. Neural Networks 69 (2015)
Lev V. Utkin
The imprecise Dirichlet model as a basis for a new boosting classification algorithm. Neurocomputing 151 (2015)
Lev V. Utkin, Frank P. A. Coolen, Sergey V. Gurov
Imprecise inference for warranty contract analysis. Reliab. Eng. Syst. Saf. 138 (2015)
Lev V. Utkin, Andrea Wiencierz
Improving over-fitting in ensemble regression by imprecise probabilities. Inf. Sci. 317 (2015)
Lev V. Utkin, Yulia A. Zhuk
Imprecise prior knowledge incorporating into one-class classification. Knowl. Inf. Syst. 41 (1) (2014)
Lev V. Utkin, Yulia A. Zhuk
Robust boosting classification models with local sets of probability distributions. Knowl. Based Syst. 61 (2014)
Lev V. Utkin, Yulia A. Zhuk, Anatoly I. Chekh
A Robust One-Class Classification Model with Interval-Valued Data Based on Belief Functions and Minimax Strategy. MLDM (2014)
Lev V. Utkin
A framework for imprecise robust one-class classification models. Int. J. Mach. Learn. Cybern. 5 (3) (2014)
Lev V. Utkin, Yulia A. Zhuk
Fuzzy decision making using the imprecise Dirichlet model. Int. J. Math. Oper. Res. 5 (1) (2013)
Lev V. Utkin, Yulia A. Zhuk
Robust novelty detection in the framework of a contamination neighbourhood. Int. J. Intell. Inf. Database Syst. 7 (3) (2013)
Lev V. Utkin
An Imprecise Boosting-like Approach to Classification. Int. J. Pattern Recognit. Artif. Intell. 27 (8) (2013)
Lev V. Utkin, Yulia A. Zhuk
Imprecise Imputation as a Tool for Solving Classification Problems with Mean Values of Unobserved Features. Adv. Artif. Intell. 2013 (2013)
Lev V. Utkin, Yulia A. Zhuk
Combining of judgments in imprecise voting multi-criteria decision problems. Int. J. Appl. Decis. Sci. 5 (3) (2012)
Van Hieu Nguyen, Lev V. Utkin, Dang Duy Thang
A Pessimistic Approach for Solving a Multi-criteria Decision Making. KSE (2012)
Lev V. Utkin, Yulia A. Zhuk
A machine learning algorithm for classification under extremely scarce information. Int. J. Data Anal. Tech. Strateg. 4 (2) (2012)
Lev V. Utkin
Fuzzy One-Class Classification Model Using Contamination Neighborhoods. Adv. Fuzzy Syst. 2012 (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Lev V. Utkin