Eugenij Moiseevich Mirkes
Orcid: 0000-0003-1474-1734
According to our database1,
Eugenij Moiseevich Mirkes
authored at least 44 papers
between 1997 and 2024.
Collaborative distances:
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Bibliography
2024
Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees.
CoRR, 2024
2023
Domain Adaptation Principal Component Analysis: Base Linear Method for Learning with Out-of-Distribution Data.
Entropy, January, 2023
Exploring the impact of social stress on the adaptive dynamics of COVID-19: Typing the behavior of naïve populations faced with epidemics.
CoRR, 2023
Proceedings of the International Joint Conference on Neural Networks, 2023
What is Hiding in Medicine's Dark Matter? Learning with Missing Data in Medical Practices.
Proceedings of the IEEE International Conference on Big Data, 2023
2022
Coloring Panchromatic Nighttime Satellite Images: Comparing the Performance of Several Machine Learning Methods.
IEEE Trans. Geosci. Remote. Sens., 2022
Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation.
Proceedings of the International Joint Conference on Neural Networks, 2022
2021
CNN-Based Spectral Super-Resolution of Panchromatic Night-Time Light Imagery: City-Size-Associated Neighborhood Effects.
Sensors, 2021
Learning from Scarce Information: Using Synthetic Data to Classify Roman Fine Ware Pottery.
Entropy, 2021
Semantic Analysis for Automated Evaluation of the Potential Impact of Research Articles.
CoRR, 2021
Proceedings of the Artificial Intelligence XXXVIII, 2021
2020
Entropy, 2020
Entropy, 2020
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data.
CoRR, 2020
How Deep Should be the Depth of Convolutional Neural Networks: a Backyard Dog Case Study.
Cogn. Comput., 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
2019
Sensors, 2019
Proceedings of the International Joint Conference on Neural Networks, 2019
2018
Inf. Sci., 2018
How deep should be the depth of convolutional neural networks: a backyard dog case study.
CoRR, 2018
Robust and scalable learning of data manifolds with complex topologies via ElPiGraph.
CoRR, 2018
Data analysis with arbitrary error measures approximated by piece-wise quadratic PQSQ functions.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018
2016
Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.
Neural Networks, 2016
Piece-wise quadratic lego set for constructing arbitrary error potentials and their fast optimization.
CoRR, 2016
Handling missing data in large healthcare dataset: A case study of unknown trauma outcomes.
Comput. Biol. Medicine, 2016
2014
Comput. Biol. Medicine, 2014
Learning optimization for decision tree classification of non-categorical data with information gain impurity criterion.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
2013
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2013
Proceedings of the Advances in Computational Intelligence, 2013
2012
Initialization of Self-Organizing Maps: Principal Components Versus Random Initialization. A Case Study
CoRR, 2012
2003
Protective Laminar Composites Design Optimisation Using Genetic Algorithm and Parallel Processing.
Proceedings of the Parallel Computing Technologies, 2003
1999
Generation of explicit knowledge from empirical data through pruning of trainable neural networks.
Proceedings of the International Joint Conference Neural Networks, 1999
1997
Proceedings of International Conference on Neural Networks (ICNN'97), 1997