Andrei V. Konstantinov

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 51

Top Topics

Gradient Boosting

Top Venues

Knowl. Based Syst.

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)
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)
Andrei V. Konstantinov, Lev V. Utkin
Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines. CoRR (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)
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, 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, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Mikhail A. Ryabinin, Anna A. Meldo
A weighted random survival forest. CoRR (2019)