Lev V. Utkin

According to our database, Lev V. Utkin authored at least 118 papers between 1996 and 2024.

Collaborative distances:

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

2024

Incorporating Expert Rules into Neural Networks in the Framework of Concept-Based Learning.

Andrei V. Konstantinov, Lev V. Utkin

CoRR, 2024

Generating Survival Interpretable Trajectories and Data.

Andrei V. Konstantinov, Stanislav R. Kirpichenko, Lev V. Utkin

CoRR, 2024

Dual feature-based and example-based explanation methods.

Andrei V. Konstantinov, Boris V. Kozlov, Stanislav R. Kirpichenko, Lev V. Utkin

CoRR, 2024

BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect.

Stanislav Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov, Vladimir Muliukha

Algorithms, 2024

2023

Interpretable ensembles of hyper-rectangles as base models.

Andrei V. Konstantinov, Lev V. Utkin

Neural Comput. Appl., October, 2023

Attention and self-attention in random forests.

Lev V. Utkin, Andrei V. Konstantinov, Stanislav R. Kirpichenko

Prog. Artif. Intell., September, 2023

Attention-like feature explanation for tabular data.

Andrei V. Konstantinov, Lev V. Utkin

Int. J. Data Sci. Anal., June, 2023

Improved Anomaly Detection by Using the Attention-Based Isolation Forest.

Lev V. Utkin, Andrey Y. Ageev, Andrei V. Konstantinov, Vladimir Muliukha

Algorithms, January, 2023

LARF: Two-Level Attention-Based Random Forests with a Mixture of Contamination Models.

Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha

Informatics, 2023

SurvBeNIM: The Beran-Based Neural Importance Model for Explaining the Survival Models.

Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov

CoRR, 2023

SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator.

Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov

CoRR, 2023

A New Computationally Simple Approach for Implementing Neural Networks with Output Hard Constraints.

Andrei V. Konstantinov, Lev V. Utkin

CoRR, 2023

Neural Attention Forests: Transformer-Based Forest Improvement.

Andrei V. Konstantinov, Lev V. Utkin, Alexey Lukashin, Vladimir Muliukha

CoRR, 2023

Multiple Instance Learning with Trainable Decision Tree Ensembles.

Andrei V. Konstantinov, Lev V. Utkin

CoRR, 2023

Multiple Instance Learning with Trainable Soft Decision Tree Ensembles.

Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha

Algorithms, 2023

Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression.

Andrei V. Konstantinov, Stanislav Kirpichenko, Lev V. Utkin

Algorithms, 2023

GBMILs: Gradient Boosting Models for Multiple Instance Learning.

Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha, Vladimir S. Zaborovsky

Proceedings of the Interactive Collaborative Robotics - 8th International Conference, 2023

2022

SurvNAM: The machine learning survival model explanation.

Lev V. Utkin, Egor D. Satyukov, Andrei V. Konstantinov

Neural Networks, 2022

Attention-based random forest and contamination model.

Lev V. Utkin, Andrei V. Konstantinov

Neural Networks, 2022

Multi-attention multiple instance learning.

Andrei V. Konstantinov, Lev V. Utkin

Neural Comput. Appl., 2022

BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect.

Stanislav R. Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov

CoRR, 2022

LARF: Two-level Attention-based Random Forests with a Mixture of Contamination Models.

Andrei V. Konstantinov, Lev V. Utkin

CoRR, 2022

Improved Anomaly Detection by Using the Attention-Based Isolation Forest.

Lev V. Utkin, Andrey Y. Ageev, Andrei V. Konstantinov

CoRR, 2022

Attention and Self-Attention in Random Forests.

Lev V. Utkin, Andrei V. Konstantinov

CoRR, 2022

Ensembles of Random SHAPs.

Lev V. Utkin, Andrei V. Konstantinov

Algorithms, 2022

AGBoost: Attention-based Modification of Gradient Boosting Machine.

Andrei V. Konstantinov, Lev V. Utkin, Stanislav Kirpichenko

Proceedings of the 31st Conference of Open Innovations Association, 2022

Multiple Instance Learning through Explanation by Using a Histopathology Example.

Andrei V. Konstantinov, Lev V. Utkin

Proceedings of the 31st Conference of Open Innovations Association, 2022

2021

Interpretable machine learning with an ensemble of gradient boosting machines.

Andrei V. Konstantinov, Lev V. Utkin

Knowl. Based Syst., 2021

Counterfactual Explanation of Machine Learning Survival Models.

Maxim Kovalev, Lev V. Utkin, Frank P. A. Coolen, Andrei V. Konstantinov

Informatica, 2021

An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data.

Lev V. Utkin, Andrei V. Konstantinov, Kirill A. Vishniakov

CoRR, 2021

Uncertainty Interpretation of the Machine Learning Survival Model Predictions.

Lev V. Utkin, Vladimir S. Zaborovsky, Maxim S. Kovalev, Andrei V. Konstantinov, Natalia A. Politaeva, Alexey Lukashin

IEEE Access, 2021

Combining an Autoencoder and a Variational Autoencoder for Explaining the Machine Learning Model Predictions.

Lev V. Utkin, Pavel D. Drobintsev, Maxim Kovalev, Andrei V. Konstantinov

Proceedings of the 28th Conference of Open Innovations Association, 2021

Gradient Boosting Machine with Partially Randomized Decision Trees.

Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha

Proceedings of the 28th Conference of Open Innovations Association, 2021

2020

A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds.

Maxim S. Kovalev, Lev V. Utkin

Neural Networks, 2020

SurvLIME: A method for explaining machine learning survival models.

Maxim S. Kovalev, Lev V. Utkin, Ernest M. Kasimov

Knowl. Based Syst., 2020

Improvement of the Deep Forest Classifier by a Set of Neural Networks.

Lev V. Utkin, Kirill D. Zhuk

Informatica (Slovenia), 2020

A New Adaptive Weighted Deep Forest and Its Modifications.

Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Anna A. Meldo

Int. J. Inf. Technol. Decis. Mak., 2020

Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors.

Lev V. Utkin, Mikhail V. Kots, Viacheslav S. Chukanov, Andrei V. Konstantinov, Anna A. Meldo

Int. J. Artif. Intell. Tools, 2020

An imprecise deep forest for classification.

Lev V. Utkin

Expert Syst. Appl., 2020

A Generalized Stacking for Implementing Ensembles of Gradient Boosting Machines.

Andrei V. Konstantinov, Lev V. Utkin

CoRR, 2020

Counterfactual explanation of machine learning survival models.

Maxim S. Kovalev, Lev V. Utkin

CoRR, 2020

Gradient boosting machine with partially randomized decision trees.

Andrei V. Konstantinov, Lev V. Utkin

CoRR, 2020

SurvLIME-Inf: A simplified modification of SurvLIME for explanation of machine learning survival models.

Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov

CoRR, 2020

Explanation of Siamese Neural Networks for Weakly Supervised Learning.

Lev V. Utkin, Maxim Kovalev, Ernest M. Kasimov

Comput. Informatics, 2020

Imprecise weighted extensions of random forests for classification and regression.

Lev V. Utkin, Maxim S. Kovalev, Frank P. A. Coolen

Appl. Soft Comput., 2020

The natural language explanation algorithms for the lung cancer computer-aided diagnosis system.

Anna A. Meldo, Lev V. Utkin, Maxim Kovalev, Ernest M. Kasimov

Artif. Intell. Medicine, 2020

Anomaly Detection Approach in Cyber Security for User and Entity Behavior Analytics System.

Vladimir Muliukha, Alexey Lukashin, Lev V. Utkin, Mikhail Popov, Anna A. Meldo

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

A deep forest classifier with weights of class probability distribution subsets.

Lev V. Utkin, Maxim Kovalev, Anna A. Meldo

Knowl. Based Syst., 2019

A weighted random survival forest.

Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Mikhail A. Ryabinin, Anna A. Meldo

Knowl. Based Syst., 2019

An imprecise extension of SVM-based machine learning models.

Lev V. Utkin

Neurocomputing, 2019

Discriminative Metric Learning with Deep Forest.

Lev V. Utkin, Mikhail A. Ryabinin

Int. J. Artif. Intell. Tools, 2019

An explanation method for Siamese neural networks.

Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov

CoRR, 2019

Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors.

Lev V. Utkin, Mikhail V. Kots, Viacheslav S. Chukanov

CoRR, 2019

An Adaptive Weighted Deep Forest Classifier.

Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Anna A. Meldo

CoRR, 2019

Imprecise Extensions of Random Forests and Random Survival Forests.

Lev V. Utkin, Maxim Kovalev, Anna A. Meldo, Frank P. A. Coolen

Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

An Ensemble of Triplet Neural Networks for Differential Diagnostics of Lung Cancer.

Lev V. Utkin, Anna A. Meldo, Maxim Kovalev, Ernest M. Kasimov

Proceedings of the 25th Conference of Open Innovations Association, 2019

A Deep Forest Improvement by Using Weighted Schemes.

Lev V. Utkin, Andrei V. Konstantinov, Anna A. Meldo, Mikhail A. Ryabinin, Viacheslav S. Chukanov

Proceedings of the 24th Conference of Open Innovations Association, 2019

Database Acquisition for the Lung Cancer Computer Aided Diagnostic Systems.

Anna A. Meldo, Lev V. Utkin, Alexey Lukashin, Vladimir Muliukha, Vladimir S. Zaborovsky

Proceedings of the 25th Conference of Open Innovations Association, 2019

2018

A robust weighted SVR-based software reliability growth model.

Lev V. Utkin, Frank P. A. Coolen

Reliab. Eng. Syst. Saf., 2018

A Siamese Deep Forest.

Lev V. Utkin, Mikhail A. Ryabinin

Knowl. Based Syst., 2018

A modification of the Lasso method by using the Bahadur representation for the genome-wide association study.

Lev V. Utkin, Yulia A. Zhuk

Informatica (Slovenia), 2018

2017

An one-class classification support vector machine model by interval-valued training data.

Lev V. Utkin, Yulia A. Zhuk

Knowl. Based Syst., 2017

Interval SVM-Based Classification Algorithm Using the Uncertainty Trick.

Lev V. Utkin, Yulia A. Zhuk

Int. J. Artif. Intell. Tools, 2017

Siamese neural network for intelligent information security control in multi-robot systems.

Lev V. Utkin, Vladimir S. Zaborovsky, Sergey G. Popov

Autom. Control. Comput. Sci., 2017

Reliability of repairable reserved systems with failure aftereffect.

Sergey V. Gurov, Lev V. Utkin

Autom. Remote. Control., 2017

2016

Binary classification SVM-based algorithms with interval-valued training data using triangular and Epanechnikov kernels.

Lev V. Utkin, Anatoly I. Chekh, Yulia A. Zhuk

Neural Networks, 2016

Detection of anomalous behavior in a robot system based on deep learning elements.

Lev V. Utkin, V. S. Zaborovskii, Sergey G. Popov

Autom. Control. Comput. Sci., 2016

2015

Imprecise inference for warranty contract analysis.

Lev V. Utkin, Frank P. A. Coolen, Sergey V. Gurov

Reliab. Eng. Syst. Saf., 2015

A new robust model of one-class classification by interval-valued training data using the triangular kernel.

Lev V. Utkin, Anatoly I. Chekh

Neural Networks, 2015

Improving over-fitting in ensemble regression by imprecise probabilities.

Lev V. Utkin, Andrea Wiencierz

Inf. Sci., 2015

The imprecise Dirichlet model as a basis for a new boosting classification algorithm.

Lev V. Utkin

Neurocomputing, 2015

Robust Classifiers Using Imprecise Probability Models and Importance of Classes.

Lev V. Utkin, Yulia A. Zhuk

Int. J. Artif. Intell. Tools, 2015

2014

A framework for imprecise robust one-class classification models.

Lev V. Utkin

Int. J. Mach. Learn. Cybern., 2014

Robust boosting classification models with local sets of probability distributions.

Lev V. Utkin, Yulia A. Zhuk

Knowl. Based Syst., 2014

Imprecise prior knowledge incorporating into one-class classification.

Lev V. Utkin, Yulia A. Zhuk

Knowl. Inf. Syst., 2014

A Robust One-Class Classification Model with Interval-Valued Data Based on Belief Functions and Minimax Strategy.

Lev V. Utkin, Yulia A. Zhuk, Anatoly I. Chekh

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2014

2013

An Imprecise Boosting-like Approach to Classification.

Lev V. Utkin

Int. J. Pattern Recognit. Artif. Intell., 2013

Fuzzy decision making using the imprecise Dirichlet model.

Lev V. Utkin, Yulia A. Zhuk

Int. J. Math. Oper. Res., 2013

Robust novelty detection in the framework of a contamination neighbourhood.

Lev V. Utkin, Yulia A. Zhuk

Int. J. Intell. Inf. Database Syst., 2013

Imprecise Imputation as a Tool for Solving Classification Problems with Mean Values of Unobserved Features.

Lev V. Utkin, Yulia A. Zhuk

Adv. Artif. Intell., 2013

2012

The DS/AHP Method under Partial Information about Criteria and Alternatives by Several Levels of Criteria.

Lev V. Utkin, Natalia V. Simanova

Int. J. Inf. Technol. Decis. Mak., 2012

A machine learning algorithm for classification under extremely scarce information.

Lev V. Utkin, Yulia A. Zhuk

Int. J. Data Anal. Tech. Strateg., 2012

Combining of judgments in imprecise voting multi-criteria decision problems.

Lev V. Utkin, Yulia A. Zhuk

Int. J. Appl. Decis. Sci., 2012

Fuzzy One-Class Classification Model Using Contamination Neighborhoods.

Lev V. Utkin

Adv. Fuzzy Syst., 2012

A Pessimistic Approach for Solving a Multi-criteria Decision Making.

Van Hieu Nguyen, Lev V. Utkin, Dang Duy Thang

Proceedings of the Fourth International Conference on Knowledge and Systems Engineering, 2012

2011

Imprecise Reliability.

Frank P. A. Coolen, Lev V. Utkin

Proceedings of the International Encyclopedia of Statistical Science, 2011

2010

Regression analysis using the imprecise Bayesian normal model.

Lev V. Utkin

Int. J. Data Anal. Tech. Strateg., 2010

2009

Computing expectations with continuous p-boxes: Univariate case.

Lev V. Utkin, Sébastien Destercke

Int. J. Approx. Reason., 2009

A new ranking procedure by incomplete pairwise comparisons using preference subsets.

Lev V. Utkin

Intell. Data Anal., 2009

2007

Imprecise reliability: An introductory overview.

Lev V. Utkin, Frank P. A. Coolen

Proceedings of the Intelligence in Reliability Engineering: New Metaheuristics, 2007

Risk Analysis under Partial Prior Information and Nonmonotone Utility Functions.

Lev V. Utkin

Int. J. Inf. Technol. Decis. Mak., 2007

Decision making under incomplete data using the imprecise Dirichlet model.

Lev V. Utkin, Thomas Augustin

Int. J. Approx. Reason., 2007

Second-order uncertainty calculations by using the imprecise Dirichlet model.

Lev V. Utkin

Intell. Data Anal., 2007

2006

Cautious Analysis of Project Risks by Interval-Valued Initial Data.

Lev V. Utkin

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2006

A method for processing the unreliable expert judgments about parameters of probability distributions.

Lev V. Utkin

Eur. J. Oper. Res., 2006

Ranking procedures by pairwise comparison using random sets and the imprecise Dirichlet model.

Lev V. Utkin

Appl. Math. Comput., 2006

2005

Computing System Reliability Given Interval-Valued Characteristics of the Components.

Lev V. Utkin, Igor Kozine

Reliab. Comput., 2005

Imprecise second-order model for a system of independent random variables.

Lev V. Utkin

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2005

Constructing imprecise probability distributions.

Igor Kozine, Lev V. Utkin

Int. J. Gen. Syst., 2005

Extensions of belief functions and possibility distributions by using the imprecise Dirichlet model.

Lev V. Utkin

Fuzzy Sets Syst., 2005

Comments on the paper "A behavioural model for vague probability assessments" by Gert de Cooman.

Lev V. Utkin

Fuzzy Sets Syst., 2005

Powerful algorithms for decision making under partial prior information and general ambiguity attitudes.

Lev V. Utkin, Thomas Augustin

Proceedings of the ISIPTA '05, 2005

2004

A new efficient algorithm for computing the imprecise reliability of monotone systems.

Lev V. Utkin

Reliab. Eng. Syst. Saf., 2004

An approach to combining unreliable pieces of evidence and their propagation in a system response analysis.

Igor Kozine, Lev V. Utkin

Reliab. Eng. Syst. Saf., 2004

Interval reliability of typical systems with partially known probabilities.

Lev V. Utkin

Eur. J. Oper. Res., 2004

Reliability models of <i>m</i>-out-of-<i>n</i> systems under incomplete information.

Lev V. Utkin

Comput. Oper. Res., 2004

2003

A second-order uncertainty model for calculation of the interval system reliability.

Lev V. Utkin

Reliab. Eng. Syst. Saf., 2003

Imprecise Second-Order Hierarchical Uncertainty Model .

Lev V. Utkin

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2003

Decision Making with Imprecise Second-Order Probabilities.

Lev V. Utkin

Proceedings of the ISIPTA '03, 2003

A Second-Order Uncertainty Model of Independent Random Variables: An Example of the Stress-Strength Reliability.

Lev V. Utkin

Proceedings of the ISIPTA '03, 2003

2002

Interval-Valued Finite Markov Chains.

Igor Kozine, Lev V. Utkin

Reliab. Comput., 2002

Stress-strength reliability models under incomplete information.

Lev V. Utkin, Igor Kozine

Int. J. Gen. Syst., 2002

2001

Computing the reliability of complex systems.

Igor Kozine, Lev V. Utkin

Proceedings of the ISIPTA '01, 2001

Different faces of the natural extension.

Igor Kozine, Lev V. Utkin

Proceedings of the ISIPTA '01, 2001

1999

Imprecise Reliability of General Structures.

Lev V. Utkin, Sergey V. Gurov

Knowl. Inf. Syst., 1999

Imprecise Reliability Models for the General Lifetime Distribution Classes.

Lev V. Utkin, Sergey V. Gurov

Proceedings of the ISIPTA '99, Proceedings of the First International Symposium on Imprecise Probabilities and Their Applications, held at the Conference Center "Het Pand" of the Universiteit Gent, Ghent, Belgium, 29 June, 1999

1998

Steady-state reliability of repairable systems by combined probability and possibility assumptions.

Lev V. Utkin, Sergey V. Gurov

Fuzzy Sets Syst., 1998

1996

A general formal approach for fuzzy reliability analysis in the possibility context.

Lev V. Utkin, Sergey V. Gurov

Fuzzy Sets Syst., 1996