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ORCIDEugenij Moiseevich Mirkes
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2020 – today
- 2024
[j19]Innokentiy Kastalskiy
, Andrei Yu. Zinovyev, Evgeny M. Mirkes, Victor B. Kazantsev, Alexander N. Gorban:
Exploring the impact of social stress on the adaptive dynamics of COVID-19: Typing the behavior of naïve populations faced with epidemics. Commun. Nonlinear Sci. Numer. Simul. 132: 107906 (2024)- [j18]Ivan Yu. Tyukin, Tatiana Tyukina, Daniël P. van Helden, Zedong Zheng, Evgeny M. Mirkes, Oliver J. Sutton, Qinghua Zhou, Alexander N. Gorban, Penelope M. Allison:
Coping with AI errors with provable guarantees. Inf. Sci. 678: 120856 (2024) - [c14]Ivan Yu. Tyukin, Tatiana Tyukina, Daniel van Helden, Zedong Zheng, Evgeny M. Mirkes, Oliver J. Sutton, Qinghua Zhou, Alexander N. Gorban, Penelope M. Allison:
Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees. IJCNN 2024: 1-8 - [i27]Ivan Yu. Tyukin, Tatiana Tyukina, Daniël P. van Helden, Zedong Zheng, Evgeny M. Mirkes, Oliver J. Sutton, Qinghua Zhou, Alexander N. Gorban, Penelope M. Allison:
Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees. CoRR abs/2402.00899 (2024) - [i26]Neslihan Suzen, Evgeny M. Mirkes, Damian Roland, Jeremy Levesley, Alexander N. Gorban, Timothy J. Coats:
What is Hiding in Medicine's Dark Matter? Learning with Missing Data in Medical Practices. CoRR abs/2402.06563 (2024) - 2023
- [j17]Evgeny M. Mirkes, Jonathan Bac, Aziz Fouché, Sergey V. Stasenko, Andrei Yu. Zinovyev, Alexander N. Gorban:
Domain Adaptation Principal Component Analysis: Base Linear Method for Learning with Out-of-Distribution Data. Entropy 25(1): 33 (2023) - [c13]Neslihan Suzen, Evgeny M. Mirkes, Damian Roland, Jeremy Levesley, Alexander N. Gorban, Timothy J. Coats:
What is Hiding in Medicine's Dark Matter? Learning with Missing Data in Medical Practices. IEEE Big Data 2023: 4979-4986 - [c12]Ying Liu, Liucheng Guo, Valeri A. Makarov, Yuxiang Huang, Alexander N. Gorban, Evgeny M. Mirkes, Ivan Yu. Tyukin:
Agile gesture recognition for capacitive sensing devices: adapting on-the-job. IJCNN 2023: 1-8 - [i25]Ying Liu, Liucheng Guo, Valeri A. Makarov, Yuxiang Huang, Alexander N. Gorban, Evgeny M. Mirkes, Ivan Yu. Tyukin:
Agile gesture recognition for capacitive sensing devices: adapting on-the-job. CoRR abs/2305.07624 (2023) - [i24]Innokentiy Kastalskiy, Andrei Yu. Zinovyev, Evgeny M. Mirkes, Victor B. Kazantsev, Alexander N. Gorban:
Exploring the impact of social stress on the adaptive dynamics of COVID-19: Typing the behavior of naïve populations faced with epidemics. CoRR abs/2311.13917 (2023) - 2022
- [j16]Natalya A. Rybnikova, Boris A. Portnov, Evgeny M. Mirkes, Andrei Yu. Zinovyev, Anna Brook, Alexander N. Gorban:
Coloring Panchromatic Nighttime Satellite Images: Comparing the Performance of Several Machine Learning Methods. IEEE Trans. Geosci. Remote. Sens. 60: 1-15 (2022) - [c11]Qinghua Zhou, Alexander N. Gorban, Evgeny M. Mirkes, Jonathan Bac, Andrei Yu. Zinovyev, Ivan Yu. Tyukin:
Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation. IJCNN 2022: 1-8 - [i23]Qinghua Zhou, Alexander N. Gorban, Evgeny M. Mirkes, Jonathan Bac, Andrei Yu. Zinovyev, Ivan Yu. Tyukin:
Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation. CoRR abs/2203.16687 (2022) - [i22]Neslihan Suzen, Alexander N. Gorban, Jeremy Levesley, Evgeny M. Mirkes:
An Informational Space Based Semantic Analysis for Scientific Texts. CoRR abs/2205.15696 (2022) - [i21]Evgeny M. Mirkes, Jonathan Bac, Aziz Fouché, Sergey V. Stasenko, Andrei Yu. Zinovyev, Alexander N. Gorban:
Domain Adaptation Principal Component Analysis: base linear method for learning with out-of-distribution data. CoRR abs/2208.13290 (2022) - 2021
- [j15]Alexander N. Gorban, Bogdan Grechuk, Evgeny M. Mirkes, Sergey V. Stasenko, Ivan Yu. Tyukin:
High-Dimensional Separability for One- and Few-Shot Learning. Entropy 23(8): 1090 (2021) - [j14]Santos J. Núñez Jareño, Daniël P. van Helden, Evgeny M. Mirkes, Ivan Yu. Tyukin, Penelope M. Allison:
Learning from Scarce Information: Using Synthetic Data to Classify Roman Fine Ware Pottery. Entropy 23(9): 1140 (2021) - [j13]Jonathan Bac, Evgeny M. Mirkes, Alexander N. Gorban, Ivan Tyukin, Andrei Yu. Zinovyev:
Scikit-Dimension: A Python Package for Intrinsic Dimension Estimation. Entropy 23(10): 1368 (2021) - [j12]Natalya A. Rybnikova, Evgeny M. Mirkes, Alexander N. Gorban:
CNN-Based Spectral Super-Resolution of Panchromatic Night-Time Light Imagery: City-Size-Associated Neighborhood Effects. Sensors 21(22): 7662 (2021) - [c10]Hossein Ghodrati Noushahr, Jeremy Levesley, Samad Ahmadi, Evgeny M. Mirkes:
GaussianProductAttributes: Density-Based Distributed Representations for Products. SGAI Conf. 2021: 139-145 - [i20]Neslihan Suzen, Alexander N. Gorban, Jeremy Levesley, Evgeny M. Mirkes:
Semantic Analysis for Automated Evaluation of the Potential Impact of Research Articles. CoRR abs/2104.12869 (2021) - [i19]Alexander N. Gorban, Bogdan Grechuk, Evgeny M. Mirkes, Sergey V. Stasenko, Ivan Yu. Tyukin:
High-dimensional separability for one- and few-shot learning. CoRR abs/2106.15416 (2021) - [i18]Santos J. Núñez Jareño, Daniël P. van Helden, Evgeny M. Mirkes, Ivan Yu. Tyukin, Penelope M. Allison:
Learning from scarce information: using synthetic data to classify Roman fine ware pottery. CoRR abs/2107.01401 (2021) - [i17]Jonathan Bac, Evgeny M. Mirkes, Alexander N. Gorban, Ivan Tyukin, Andrei Yu. Zinovyev:
Scikit-dimension: a Python package for intrinsic dimension estimation. CoRR abs/2109.02596 (2021) - 2020
- [j11]Alexander N. Gorban, Evgeny M. Mirkes, Ivan Yu. Tyukin:
How Deep Should be the Depth of Convolutional Neural Networks: a Backyard Dog Case Study. Cogn. Comput. 12(2): 388-397 (2020) - [j10]Evgeny M. Mirkes:
Universal Gorban's Entropies: Geometric Case Study. Entropy 22(3): 264 (2020) - [j9]Luca Albergante, Evgeny M. Mirkes, Jonathan Bac, Huidong Chen, Alexis Martin, Louis Faure, Emmanuel Barillot, Luca Pinello, Alexander N. Gorban, Andrei Yu. Zinovyev:
Robust and Scalable Learning of Complex Intrinsic Dataset Geometry via ElPiGraph. Entropy 22(3): 296 (2020) - [j8]Evgeny M. Mirkes, Jeza Allohibi, Alexander N. Gorban:
Fractional Norms and Quasinorms Do Not Help to Overcome the Curse of Dimensionality. Entropy 22(10): 1105 (2020) - [c9]Evgeny M. Mirkes:
Artificial Neural Network Pruning to Extract Knowledge. IJCNN 2020: 1-8 - [i16]Neslihan Suzen, Evgeny M. Mirkes, Alexander N. Gorban:
Informational Space of Meaning for Scientific Texts. CoRR abs/2004.13717 (2020) - [i15]Evgeny M. Mirkes, Jeza Allohibi, Alexander N. Gorban:
Fractional norms and quasinorms do not help to overcome the curse of dimensionality. CoRR abs/2004.14230 (2020) - [i14]Evgeny M. Mirkes:
Artificial Neural Network Pruning to Extract Knowledge. CoRR abs/2005.06284 (2020) - [i13]Sergey E. Golovenkin, Jonathan Bac, Alexander Chervov, Evgeny M. Mirkes, Yuliya V. Orlova, Emmanuel Barillot, Alexander N. Gorban, Andrei Yu. Zinovyev:
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data. CoRR abs/2007.03788 (2020) - [i12]Neslihan Suzen, Alexander N. Gorban, Jeremy Levesley, Evgeny M. Mirkes:
Principal Components of the Meaning. CoRR abs/2009.08859 (2020)
2010 – 2019
- 2019
- [j7]Petra J. Jones, Evgeny M. Mirkes, Tom Yates, Charlotte L. Edwardson, Mike Catt, Melanie J. Davies, Kamlesh Khunti, Alex V. Rowlands:
Towards a Portable Model to Discriminate Activity Clusters from Accelerometer Data. Sensors 19(20): 4504 (2019) - [c8]Evgeny M. Mirkes, Jeza Allohibi, Alexander N. Gorban:
Do Fractional Norms and Quasinorms Help to Overcome the Curse of Dimensionality? IJCNN 2019: 1-8 - [i11]Neslihan Suzen, Evgeny M. Mirkes, Alexander N. Gorban:
LScDC-new large scientific dictionary. CoRR abs/1912.06858 (2019) - 2018
- [j6]Alexander N. Gorban, A. Golubkov, Bogdan Grechuk, Eugenij Moiseevich Mirkes, Ivan Tyukin:
Correction of AI systems by linear discriminants: Probabilistic foundations. Inf. Sci. 466: 303-322 (2018) - [c7]Alexander N. Gorban, Evgeny M. Mirkes, Andrei Yu. Zinovyev:
Data analysis with arbitrary error measures approximated by piece-wise quadratic PQSQ functions. IJCNN 2018: 1-8 - [i10]Luca Albergante, Evgeny M. Mirkes, Huidong Chen, Alexis Martin, Louis Faure, Emmanuel Barillot, Luca Pinello, Alexander N. Gorban, Andrei Yu. Zinovyev:
Robust and scalable learning of data manifolds with complex topologies via ElPiGraph. CoRR abs/1804.07580 (2018) - [i9]Alexander N. Gorban, Evgeny M. Mirkes, I. Y. Tukin:
How deep should be the depth of convolutional neural networks: a backyard dog case study. CoRR abs/1805.01516 (2018) - [i8]Neslihan Suzen, Alexander N. Gorban, Jeremy Levesley, Evgeny M. Mirkes:
Automatic Short Answer Grading and Feedback Using Text Mining Methods. CoRR abs/1807.10543 (2018) - [i7]Alexander N. Gorban, A. Golubkov, Bogdan Grechuk, Evgeny M. Mirkes, Ivan Yu. Tyukin:
Correction of AI systems by linear discriminants: Probabilistic foundations. CoRR abs/1811.05321 (2018) - 2016
- [j5]Eugenij Moiseevich Mirkes, Timothy J. Coats, Jeremy Levesley, Alexander N. Gorban:
Handling missing data in large healthcare dataset: A case study of unknown trauma outcomes. Comput. Biol. Medicine 75: 203-216 (2016) - [j4]Ayodeji A. Akinduko, Evgeny M. Mirkes, Alexander N. Gorban:
SOM: Stochastic initialization versus principal components. Inf. Sci. 364-365: 213-221 (2016) - [j3]Alexander N. Gorban, Eugenij Moiseevich Mirkes, Andrei Yu. Zinovyev:
Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning. Neural Networks 84: 28-38 (2016) - [i6]Alexander N. Gorban, Eugenij Moiseevich Mirkes, Andrei Yu. Zinovyev:
Robust principal graphs for data approximation. CoRR abs/1603.06828 (2016) - [i5]Alexander N. Gorban, Eugenij Moiseevich Mirkes, Andrei Yu. Zinovyev:
Piece-wise quadratic lego set for constructing arbitrary error potentials and their fast optimization. CoRR abs/1605.06276 (2016) - 2014
- [j2]Eugenij Moiseevich Mirkes, I. Alexandrakis, K. Slater, R. Tuli, Alexander N. Gorban:
Computational diagnosis and risk evaluation for canine lymphoma. Comput. Biol. Medicine 53: 279-290 (2014) - [c6]Konstantin I. Sofeikov, Ivan Tyukin, Alexander N. Gorban, Eugenij Moiseevich Mirkes, Danil V. Prokhorov, Ilya V. Romanenko:
Learning optimization for decision tree classification of non-categorical data with information gain impurity criterion. IJCNN 2014: 3548-3555 - 2013
- [j1]Andrei Yu. Zinovyev, Evgeny M. Mirkes:
Data complexity measured by principal graphs. Comput. Math. Appl. 65(10): 1471-1482 (2013) - [c5]Evgeny M. Mirkes, Andrei Yu. Zinovyev, Alexander N. Gorban:
Geometrical Complexity of Data Approximators. IWANN (1) 2013: 500-509 - [c4]Michael G. Sadovsky, Eugene Mirkes:
New Structure in Genomes Manifests in Triplet Distribution Alongside a Sequence. IWBBIO 2013: 89-97 - [i4]Eugenij Moiseevich Mirkes, Andrei Yu. Zinovyev, Alexander N. Gorban:
Geometrical complexity of data approximators. CoRR abs/1302.2645 (2013) - 2012
- [i3]A. A. Akinduko, Evgeny M. Mirkes:
Initialization of Self-Organizing Maps: Principal Components Versus Random Initialization. A Case Study. CoRR abs/1210.5873 (2012) - [i2]Andrei Yu. Zinovyev, Evgeny M. Mirkes:
Data complexity measured by principal graphs. CoRR abs/1212.5841 (2012)
2000 – 2009
- 2003
- [c3]Mikhail Alexandrovich Vishnevsky, Vladimir Dmitrievich Koshur, Alexander Ivanovich Legalov, Eugenij Moiseevich Mirkes:
Protective Laminar Composites Design Optimisation Using Genetic Algorithm and Parallel Processing. PaCT 2003: 394-400 - [i1]Alexander N. Gorban, Eugenij Moiseevich Mirkes, Victor G. Tsaregorodtsev:
Generation of Explicit Knowledge from Empirical Data through Pruning of Trainable Neural Networks. CoRR cond-mat/0307083 (2003)
1990 – 1999
- 1999
- [c2]Alexander N. Gorban, Evgeny M. Mirkes, Victor G. Tsaregorodtsev:
Generation of explicit knowledge from empirical data through pruning of trainable neural networks. IJCNN 1999: 4393-4398 - 1997
- [c1]Alexander N. Gorban, Yeugenii M. Mirkes, Donald C. Wunsch II:
High order orthogonal tensor networks: information capacity and reliability. ICNN 1997: 1311-1314
Coauthor Index
aka: Ivan Yu. Tyukin
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