Eugenij Moiseevich Mirkes

Orcid: 0000-0003-1474-1734

According to our database1, Eugenij Moiseevich Mirkes authored at least 46 papers between 1997 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Coping with AI errors with provable guarantees.
Inf. Sci., 2024

Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees.
CoRR, 2024

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., 2024

Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
Domain Adaptation Principal Component Analysis: Base Linear Method for Learning with Out-of-Distribution Data.
Entropy, January, 2023

Agile gesture recognition for capacitive sensing devices: adapting on-the-job.
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

An Informational Space Based Semantic Analysis for Scientific Texts.
CoRR, 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

High-Dimensional Separability for One- and Few-Shot Learning.
Entropy, 2021

Scikit-Dimension: A Python Package for Intrinsic Dimension Estimation.
Entropy, 2021

Semantic Analysis for Automated Evaluation of the Potential Impact of Research Articles.
CoRR, 2021

GaussianProductAttributes: Density-Based Distributed Representations for Products.
Proceedings of the Artificial Intelligence XXXVIII, 2021

2020
Fractional Norms and Quasinorms Do Not Help to Overcome the Curse of Dimensionality.
Entropy, 2020

Universal Gorban's Entropies: Geometric Case Study.
Entropy, 2020

Robust and Scalable Learning of Complex Intrinsic Dataset Geometry via ElPiGraph.
Entropy, 2020

Principal Components of the Meaning.
CoRR, 2020

Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data.
CoRR, 2020

Informational Space of Meaning for Scientific Texts.
CoRR, 2020

How Deep Should be the Depth of Convolutional Neural Networks: a Backyard Dog Case Study.
Cogn. Comput., 2020

Artificial Neural Network Pruning to Extract Knowledge.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
Towards a Portable Model to Discriminate Activity Clusters from Accelerometer Data.
Sensors, 2019

LScDC-new large scientific dictionary.
CoRR, 2019

Do Fractional Norms and Quasinorms Help to Overcome the Curse of Dimensionality?
Proceedings of the International Joint Conference on Neural Networks, 2019

2018
Correction of AI systems by linear discriminants: Probabilistic foundations.
Inf. Sci., 2018

Automatic Short Answer Grading and Feedback Using Text Mining Methods.
CoRR, 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

SOM: Stochastic initialization versus principal components.
Inf. Sci., 2016

Piece-wise quadratic lego set for constructing arbitrary error potentials and their fast optimization.
CoRR, 2016

Robust principal graphs for data approximation.
CoRR, 2016

Handling missing data in large healthcare dataset: A case study of unknown trauma outcomes.
Comput. Biol. Medicine, 2016

2014
Computational diagnosis and risk evaluation for canine lymphoma.
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
Data complexity measured by principal graphs.
Comput. Math. Appl., 2013

New Structure in Genomes Manifests in Triplet Distribution Alongside a Sequence.
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2013

Geometrical Complexity of Data Approximators.
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
High order orthogonal tensor networks: information capacity and reliability.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997


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