Ivan Tyukin
Orcid: 0000000273597966
According to our database^{1},
Ivan Tyukin
authored at least 72 papers
between 2000 and 2024.
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Bibliography
2024
Commun. Nonlinear Sci. Numer. Simul., April, 2024
IEEE Trans. Software Eng., March, 2024
Inf. Sci., 2024
CoRR, 2024
Agile gesture recognition for lowpower applications: customisation for generalisation.
CoRR, 2024
Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees.
CoRR, 2024
2023
Int. J. Geogr. Inf. Sci., December, 2023
MyINet: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images.
Entropy, March, 2023
Computer, February, 2023
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 lowsample highdimensional 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
2022
Towards a mathematical understanding of learning from few examples with nonlinear feature maps.
CoRR, 2022
CoRR, 2022
Quasiorthogonality and intrinsic dimensions as measures of learning and generalisation.
Proceedings of the International Joint Conference on Neural Networks, 2022
2021
Neural Networks, 2021
Inf. Sci., 2021
Advances in Data Preprocessing for Biomedical Data Fusion: An Overview of the Methods, Challenges, and Prospects.
Inf. Fusion, 2021
Learning from Scarce Information: Using Synthetic Data to Classify Roman Fine Ware Pottery.
Entropy, 2021
Entropy, 2021
Entropy, 2021
CoRR, 2021
Efficient state synchronisation in modelbased testing through reinforcement learning.
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021
Proceedings of the International Joint Conference on Neural Networks, 2021
2020
Entropy, 2020
How Deep Should be the Depth of Convolutional Neural Networks: a Backyard Dog Case Study.
Cogn. Comput., 2020
Myocardial Infarction Detection and Quantification Based on a Convolution Neural Network with Online Error Correction Capabilities.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Neural Networks for the Retrieval of Methane from the Sentinel5 Precursor Satellite.
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
CoRR, 2019
CoRR, 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
2018
Inf. Sci., 2018
Frontiers Neurorobotics, 2018
The unreasonable effectiveness of small neural ensembles in highdimensional brain.
CoRR, 2018
CoRR, 2018
Blessing of dimensionality: mathematical foundations of the statistical physics of data.
CoRR, 2018
Appl. Soft Comput., 2018
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
2017
Neural Networks, 2017
2016
Inf. Sci., 2016
CoRR, 2016
2015
Phase Selective Oscillations in Two Noise Driven Synaptically Coupled Spiking Neurons.
Int. J. Bifurc. Chaos, 2015
2014
CoRR, 2014
Learning optimization for decision tree classification of noncategorical 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 Lyapunovlike conditions of forward invariance and boundedness for a class of unstable systems.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014
2013
Lyapunovlike Conditions of Forward Invariance and Boundedness for a Class of Unstable Systems.
SIAM J. Control. Optim., 2013
Adaptive observers and parameter estimation for a class of systems nonlinear in the parameters.
Autom., 2013
Explicit reducedorder 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
2010
Int. J. Neural Syst., 2010
CoRR, 2010
2009
Invariant template matching in systems with spatiotemporal coding: A matter of instability.
Neural Networks, 2009
Proceedings of the IEEE International Conference on Control Applications, 2009
2008
SIAM J. Control. Optim., 2008
Adaptive Classification of Temporal Signals in FixedWeight Recurrent Neural Networks: An Existence Proof.
Neural Comput., 2008
Proceedings of the 47th IEEE Conference on Decision and Control, 2008
2007
Adaptation and Parameter Estimation in Systems With Unstable Target Dynamics and Nonlinear Parametrization.
IEEE Trans. Autom. Control., 2007
Invariant template matching in systems with spatiotemporal coding: a vote for instability
CoRR, 2007
2005
Proceedings of the American Control Conference, 2005
2003
IEEE Trans. Autom. Control., 2003
Neural Comput., 2003
Proceedings of the 7th European Control Conference, 2003
2002
On a problem of timevarying learning rate influence on the adaptive system dynamics.
Proceedings of the 41st IEEE Conference on Decision and Control, 2002
2000
Proceedings of the 39th IEEE Conference on Decision and Control, 2000