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ORCIDAndrei V. Konstantinov
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2020 – today
- 2024
[j18]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): 40 (2024)- [i27]Andrei V. Konstantinov, Boris V. Kozlov, Stanislav R. Kirpichenko, Lev V. Utkin:
Dual feature-based and example-based explanation methods. CoRR abs/2401.16294 (2024) - [i26]Andrei V. Konstantinov, Stanislav R. Kirpichenko, Lev V. Utkin:
Generating Survival Interpretable Trajectories and Data. CoRR abs/2402.12331 (2024) - [i25]Andrei V. Konstantinov, Lev V. Utkin:
Incorporating Expert Rules into Neural Networks in the Framework of Concept-Based Learning. CoRR abs/2402.14726 (2024) - [i24]Lev V. Utkin, Andrei V. Konstantinov, Stanislav R. Kirpichenko:
FI-CBL: A Probabilistic Method for Concept-Based Learning with Expert Rules. CoRR abs/2406.19897 (2024) - 2023
- [j17]Lev V. Utkin, Andrey Y. Ageev, Andrei V. Konstantinov, Vladimir Muliukha:
Improved Anomaly Detection by Using the Attention-Based Isolation Forest. Algorithms 16(1): 19 (2023) - [j16]Andrei V. Konstantinov, Stanislav Kirpichenko, Lev V. Utkin:
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression. Algorithms 16(5): 226 (2023) - [j15]Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha:
Multiple Instance Learning with Trainable Soft Decision Tree Ensembles. Algorithms 16(8): 358 (2023) - [j14]Andrei V. Konstantinov, Lev V. Utkin:
Attention-like feature explanation for tabular data. Int. J. Data Sci. Anal. 16(1): 1-26 (2023) - [j13]Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha:
LARF: Two-Level Attention-Based Random Forests with a Mixture of Contamination Models. Informatics 10(2): 40 (2023) - [j12]Andrei V. Konstantinov, Lev V. Utkin:
Interpretable ensembles of hyper-rectangles as base models. Neural Comput. Appl. 35(29): 21771-21795 (2023) - [j11]Lev V. Utkin, Andrei V. Konstantinov, Stanislav R. Kirpichenko:
Attention and self-attention in random forests. Prog. Artif. Intell. 12(3): 257-273 (2023) - [c6]Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha, Vladimir S. Zaborovsky:
GBMILs: Gradient Boosting Models for Multiple Instance Learning. ICR 2023: 233-245 - [i23]Andrei V. Konstantinov, Lev V. Utkin:
Multiple Instance Learning with Trainable Decision Tree Ensembles. CoRR abs/2302.06601 (2023) - [i22]Andrei V. Konstantinov, Lev V. Utkin:
Interpretable Ensembles of Hyper-Rectangles as Base Models. CoRR abs/2303.08625 (2023) - [i21]Andrei V. Konstantinov, Lev V. Utkin, Alexey Lukashin, Vladimir Muliukha:
Neural Attention Forests: Transformer-Based Forest Improvement. CoRR abs/2304.05980 (2023) - [i20]Andrei V. Konstantinov, Lev V. Utkin:
A New Computationally Simple Approach for Implementing Neural Networks with Output Hard Constraints. CoRR abs/2307.10459 (2023) - [i19]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 abs/2308.03730 (2023) - [i18]Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov:
SurvBeNIM: The Beran-Based Neural Importance Model for Explaining the Survival Models. CoRR abs/2312.06638 (2023) - 2022
- [j10]Lev V. Utkin, Andrei V. Konstantinov:
Ensembles of Random SHAPs. Algorithms 15(11): 431 (2022) - [j9]Andrei V. Konstantinov, Lev V. Utkin:
Multi-attention multiple instance learning. Neural Comput. Appl. 34(16): 14029-14051 (2022) - [j8]Lev V. Utkin, Egor D. Satyukov, Andrei V. Konstantinov:
SurvNAM: The machine learning survival model explanation. Neural Networks 147: 81-102 (2022) - [j7]Lev V. Utkin, Andrei V. Konstantinov:
Attention-based random forest and contamination model. Neural Networks 154: 346-359 (2022) - [c5]Andrei V. Konstantinov, Lev V. Utkin, Stanislav Kirpichenko:
AGBoost: Attention-based Modification of Gradient Boosting Machine. FRUCT 2022: 96-101 - [c4]Andrei V. Konstantinov, Lev V. Utkin:
Multiple Instance Learning through Explanation by Using a Histopathology Example. FRUCT 2022: 102-108 - [i17]Lev V. Utkin, Andrei V. Konstantinov:
Attention-based Random Forest and Contamination Model. CoRR abs/2201.02880 (2022) - [i16]Lev V. Utkin, Andrei V. Konstantinov:
Attention and Self-Attention in Random Forests. CoRR abs/2207.04293 (2022) - [i15]Andrei V. Konstantinov, Lev V. Utkin, Stanislav Kirpichenko:
AGBoost: Attention-based Modification of Gradient Boosting Machine. CoRR abs/2207.05724 (2022) - [i14]Andrei V. Konstantinov, Stanislav R. Kirpichenko, Lev V. Utkin:
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression. CoRR abs/2207.09139 (2022) - [i13]Lev V. Utkin, Andrey Y. Ageev, Andrei V. Konstantinov:
Improved Anomaly Detection by Using the Attention-Based Isolation Forest. CoRR abs/2210.02558 (2022) - [i12]Andrei V. Konstantinov, Lev V. Utkin:
LARF: Two-level Attention-based Random Forests with a Mixture of Contamination Models. CoRR abs/2210.05168 (2022) - [i11]Stanislav R. Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov:
BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect. CoRR abs/2211.10793 (2022) - 2021
- [j6]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: 120158-120175 (2021) - [j5]Maxim Kovalev, Lev V. Utkin, Frank P. A. Coolen, Andrei V. Konstantinov:
Counterfactual Explanation of Machine Learning Survival Models. Informatica 32(4): 817-847 (2021) - [j4]Andrei V. Konstantinov, Lev V. Utkin:
Interpretable machine learning with an ensemble of gradient boosting machines. Knowl. Based Syst. 222: 106993 (2021) - [c3]Andrei V. Konstantinov, Lev V. Utkin, Vladimir Muliukha:
Gradient Boosting Machine with Partially Randomized Decision Trees. FRUCT 2021: 167-173 - [c2]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: 489-494 - [i10]Lev V. Utkin, Andrei V. Konstantinov:
Ensembles of Random SHAPs. CoRR abs/2103.03302 (2021) - [i9]Lev V. Utkin, Egor D. Satyukov, Andrei V. Konstantinov:
SurvNAM: The machine learning survival model explanation. CoRR abs/2104.08903 (2021) - [i8]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 abs/2106.09111 (2021) - [i7]Andrei V. Konstantinov, Lev V. Utkin:
Attention-like feature explanation for tabular data. CoRR abs/2108.04855 (2021) - [i6]Andrei V. Konstantinov, Lev V. Utkin:
Multi-Attention Multiple Instance Learning. CoRR abs/2112.06071 (2021) - 2020
- [j3]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): 2050005:1-2050005:23 (2020) - [j2]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): 963-986 (2020) - [i5]Andrei V. Konstantinov, Lev V. Utkin:
Gradient boosting machine with partially randomized decision trees. CoRR abs/2006.11014 (2020) - [i4]Andrei V. Konstantinov, Lev V. Utkin:
A Generalized Stacking for Implementing Ensembles of Gradient Boosting Machines. CoRR abs/2010.06026 (2020) - [i3]Andrei V. Konstantinov, Lev V. Utkin:
Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines. CoRR abs/2010.07388 (2020)
2010 – 2019
- 2019
- [j1]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: 136-144 (2019) - [c1]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: 451-456 - [i2]Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Mikhail A. Ryabinin, Anna A. Meldo:
A weighted random survival forest. CoRR abs/1901.00213 (2019) - [i1]Lev V. Utkin, Andrei V. Konstantinov, Viacheslav S. Chukanov, Mikhail V. Kots, Anna A. Meldo:
An Adaptive Weighted Deep Forest Classifier. CoRR abs/1901.01334 (2019)
Coauthor Index
aka: Stanislav R. Kirpichenko
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