Andrei V. Konstantinov

According to our database, Andrei V. Konstantinov authored at least 40 papers between 2019 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 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

A Generalized Stacking for Implementing Ensembles of Gradient Boosting Machines.

Andrei V. Konstantinov, Lev V. Utkin

CoRR, 2020

Gradient boosting machine with partially randomized decision trees.

Andrei V. Konstantinov, Lev V. Utkin

CoRR, 2020

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 Adaptive Weighted Deep Forest Classifier.

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

CoRR, 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