Alexander N. Gorban
Orcid: 0000-0001-6224-1430Affiliations:
- University of Leicester, Department of Mathematics, UK
According to our database1,
Alexander N. Gorban
authored at least 107 papers
between 1997 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on zbmath.org
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on orcid.org
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on id.loc.gov
On csauthors.net:
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
The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning.
CoRR, 2023
CoRR, 2023
Neuromorphic tuning of feature spaces to overcome the challenge of low-sample high-dimensional data.
Proceedings of the International Joint Conference on Neural Networks, 2023
Proceedings of the International Joint Conference on Neural Networks, 2023
Proceedings of the Geometric Science of Information - 6th International Conference, 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
Frontiers Neurorobotics, September, 2022
Coloring Panchromatic Nighttime Satellite Images: Comparing the Performance of Several Machine Learning Methods.
IEEE Trans. Geosci. Remote. Sens., 2022
Neural Comput. Appl., 2022
HUM3DIL: Semi-supervised Multi-modal 3D Human Pose Estimation for Autonomous Driving.
CoRR, 2022
Towards a mathematical understanding of learning from few examples with nonlinear feature maps.
CoRR, 2022
Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation.
Proceedings of the International Joint Conference on Neural Networks, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022
Proceedings of the Conference on Robot Learning, 2022
2021
CNN-Based Spectral Super-Resolution of Panchromatic Night-Time Light Imagery: City-Size-Associated Neighborhood Effects.
Sensors, 2021
Inf. Sci., 2021
CoRR, 2021
Semantic Analysis for Automated Evaluation of the Potential Impact of Research Articles.
CoRR, 2021
Proceedings of the International Joint Conference on Neural Networks, 2021
Proceedings of the International Joint Conference on Neural Networks, 2021
2020
Correction to: Multivariate Gaussian and Student-t process regression for multi-output prediction.
Neural Comput. Appl., 2020
Neural Comput. Appl., 2020
Entropy, 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 IEEE Winter Conference on Applications of Computer Vision, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
2019
Fast construction of correcting ensembles for legacy Artificial Intelligence systems: Algorithms and a case study.
Inf. Sci., 2019
Inf. Sci., 2019
Commun. Nonlinear Sci. Numer. Simul., 2019
Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics.
Proceedings of the Recent Advances in Big Data and Deep Learning, 2019
Kernel Stochastic Separation Theorems and Separability Characterizations of Kernel Classifiers.
Proceedings of the International Joint Conference on Neural Networks, 2019
Proceedings of the International Joint Conference on Neural Networks, 2019
2018
Inf. Sci., 2018
Frontiers Neurorobotics, 2018
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
Blessing of dimensionality: mathematical foundations of the statistical physics of data.
CoRR, 2018
Proceedings of the 2018 International Joint Conference on Neural Networks, 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
Proceedings of the 20th IEEE International Conference on High Performance Computing and Communications; 16th IEEE International Conference on Smart City; 4th IEEE International Conference on Data Science and Systems, 2018
Proceedings of the Computer Vision - ACCV 2018, 2018
2017
Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition, 2017
2016
Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.
Neural Networks, 2016
CoRR, 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
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016
2015
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015
Fast and user-friendly non-linear principal manifold learning by method of elastic maps.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015
2014
ViDaExpert: user-friendly tool for nonlinear visualization and analysis of multidimensional vectorial data.
CoRR, 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
Scene analysis assisting for AWB using binary decision trees and average image metrics.
Proceedings of the IEEE International Conference on Consumer Electronics, 2014
Further results on Lyapunov-like conditions of forward invariance and boundedness for a class of unstable systems.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014
2013
Lyapunov-like Conditions of Forward Invariance and Boundedness for a Class of Unstable Systems.
SIAM J. Control. Optim., 2013
Comput. Math. Appl., 2013
Proceedings of the Advances in Computational Intelligence, 2013
Explicit reduced-order integral formulations of state and parameter estimation problems for a class of nonlinear systems.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013
2011
2010
Principal Manifolds and Graphs in Practice: from Molecular Biology to Dynamical Systems.
Int. J. Neural Syst., 2010
BMC Syst. Biol., 2010
2008
2007
Numer. Algorithms, 2007
Proceedings of the International Joint Conference on Neural Networks, 2007
2005
Four basic symmetry types in the universal 7-cluster structure of microbial genomic sequences.
Silico Biol., 2005
Computing, 2005
2004
MultiNeuron - Neural Networks Simulator For Medical, Physiological, and Psychological Applications
CoRR, 2004
2003
Open Syst. Inf. Dyn., 2003
Neural network modeling of data with gaps: method of principal curves Carleman's formula, and other
CoRR, 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
Proceedings of International Conference on Neural Networks (ICNN'97), 1997