Ivan Yu. Tyukin

64 papers A* 1B 8C 1Journal 49Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Theoretical Advances on Stochastic Configuration Networks. IEEE Trans. Neural Networks Learn. Syst. Xiufeng Yan, Dianhui Wang, Ivan Yu. Tyukin
2025	J	`jnl`	Situation-Based Neuromorphic Memory in Spiking Neuron-Astrocyte Network. IEEE Trans. Neural Networks Learn. Syst. Susanna Yu Gordleeva, Yuliya Tsybina, Mikhail Krivonosov, Ivan Yu. Tyukin, Victor B. Kazantsev, Alexey Zaikin, Alexander N. Gorban
2025	J	`jnl`	Staining and locking computer vision models without retraining. CoRR Oliver J. Sutton, Qinghua Zhou, George Leete, Alexander N. Gorban, Ivan Yu. Tyukin
2025	J	`jnl`	StepProof: Step-by-step verification of natural language mathematical proofs. CoRR Xiaolin Hu, Qinghua Zhou, Bogdan Grechuk, Ivan Yu. Tyukin
2025	J	`jnl`	When fractional quasi p-norms concentrate. CoRR Ivan Yu. Tyukin, Bogdan Grechuk, Evgeny M. Mirkes, Alexander N. Gorban
2024	J	`jnl`	Accelerating Finite State Machine-Based Testing Using Reinforcement Learning. IEEE Trans. Software Eng. Uraz Cengiz Türker, Robert M. Hierons, Khaled El-Fakih, Mohammad Reza Mousavi, Ivan Yu. Tyukin
2024	J	`jnl`	Agile gesture recognition for low-power applications: customisation for generalisation. CoRR Ying Liu, Liucheng Guo, Valeri A. Makarov, Alexander Gorbana, Evgeny Mirkesa, Ivan Yu. Tyukin
2024	J	`jnl`	Coping with AI errors with provable guarantees. Inf. Sci. 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
2024	J	`jnl`	How adversarial attacks can disrupt seemingly stable accurate classifiers. Neural Networks Oliver J. Sutton, Qinghua Zhou, Ivan Yu. Tyukin, Alexander N. Gorban, Alexander Bastounis, Desmond J. Higham
2024	J	`jnl`	Stealth edits for provably fixing or attacking large language models. CoRR Oliver J. Sutton, Qinghua Zhou, Wei Wang, Desmond J. Higham, Alexander N. Gorban, Alexander Bastounis, Ivan Yu. Tyukin
2024	B	`conf`	Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees. IJCNN Ivan Yu. Tyukin, Tatiana Tyukina, Daniel van Helden, Zedong Zheng, Evgeny M. Mirkes, Oliver J. Sutton, Qinghua Zhou, Alexander N. Gorban, Penelope M. Allison
2024	J	`jnl`	Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees. CoRR 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
2023	—	`conf`	A Geometric View on the Role of Nonlinear Feature Maps in Few-Shot Learning. GSI (1) Oliver J. Sutton, Alexander N. Gorban, Ivan Yu. Tyukin
2023	B	`conf`	Agile gesture recognition for capacitive sensing devices: adapting on-the-job. IJCNN Ying Liu, Liucheng Guo, Valeri A. Makarov, Yuxiang Huang, Alexander N. Gorban, Evgeny M. Mirkes, Ivan Yu. Tyukin
2023	J	`jnl`	Agile gesture recognition for capacitive sensing devices: adapting on-the-job. CoRR Ying Liu, Liucheng Guo, Valeri A. Makarov, Yuxiang Huang, Alexander N. Gorban, Evgeny M. Mirkes, Ivan Yu. Tyukin
2023	J	`jnl`	How adversarial attacks can disrupt seemingly stable accurate classifiers. CoRR Oliver J. Sutton, Qinghua Zhou, Ivan Yu. Tyukin, Alexander N. Gorban, Alexander Bastounis, Desmond J. Higham
2023	J	`jnl`	MyI-Net: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images. Entropy Shuihua Wang, Ahmed M. S. E. K. Abdelaty, Kelly Parke, Jayanth Ranjit Arnold, Gerry P. McCann, Ivan Yu. Tyukin
2023	B	`conf`	Neuromorphic tuning of feature spaces to overcome the challenge of low-sample high-dimensional data. IJCNN Qinghua Zhou, Oliver J. Sutton, Yudong Zhang, Alexander N. Gorban, Valeri A. Makarov, Ivan Yu. Tyukin
2023	—	`conf`	Relative Intrinsic Dimensionality Is Intrinsic to Learning. ICANN (1) Oliver J. Sutton, Qinghua Zhou, Alexander N. Gorban, Ivan Yu. Tyukin
2023	J	`jnl`	Relative intrinsic dimensionality is intrinsic to learning. CoRR Oliver J. Sutton, Qinghua Zhou, Alexander N. Gorban, Ivan Yu. Tyukin
2023	—	`conf`	The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning. ICANN (1) Alexander Bastounis, Alexander N. Gorban, Anders C. Hansen, Desmond J. Higham, Danil V. Prokhorov, Oliver J. Sutton, Ivan Yu. Tyukin, Qinghua Zhou
2023	J	`jnl`	The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning. CoRR Alexander Bastounis, Alexander N. Gorban, Anders C. Hansen, Desmond J. Higham, Danil V. Prokhorov, Oliver J. Sutton, Ivan Yu. Tyukin, Qinghua Zhou
2022	J	`jnl`	Learning from few examples with nonlinear feature maps. CoRR Ivan Yu. Tyukin, Oliver J. Sutton, Alexander N. Gorban
2022	J	`jnl`	MyI-Net: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images. CoRR Shuihua Wang, Ahmed M. S. E. K. Abdelaty, Kelly Parke, Jayanth Ranjit Arnold, Gerry P. McCann, Ivan Yu. Tyukin
2022	B	`conf`	Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation. IJCNN Qinghua Zhou, Alexander N. Gorban, Evgeny M. Mirkes, Jonathan Bac, Andrei Yu. Zinovyev, Ivan Yu. Tyukin
2022	J	`jnl`	Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation. CoRR Qinghua Zhou, Alexander N. Gorban, Evgeny M. Mirkes, Jonathan Bac, Andrei Yu. Zinovyev, Ivan Yu. Tyukin
2022	J	`jnl`	Towards a mathematical understanding of learning from few examples with nonlinear feature maps. CoRR Oliver J. Sutton, Alexander N. Gorban, Ivan Yu. Tyukin
2021	J	`jnl`	Blessing of dimensionality at the edge and geometry of few-shot learning. Inf. Sci. Ivan Yu. Tyukin, Alexander N. Gorban, Alistair A. McEwan, Sepehr Meshkinfamfard, Lixin Tang
2021	B	`conf`	Demystification of Few-shot and One-shot Learning. IJCNN Ivan Yu. Tyukin, Alexander N. Gorban, Muhammad H. Alkhudaydi, Qinghua Zhou
2021	J	`jnl`	Demystification of Few-shot and One-shot Learning. CoRR Ivan Yu. Tyukin, Alexander N. Gorban, Muhammad H. Alkhudaydi, Qinghua Zhou
2021	A*	`conf`	Efficient state synchronisation in model-based testing through reinforcement learning. ASE Uraz Cengiz Türker, Robert M. Hierons, Mohammad Reza Mousavi, Ivan Yu. Tyukin
2021	J	`jnl`	General stochastic separation theorems with optimal bounds. Neural Networks Bogdan Grechuk, Alexander N. Gorban, Ivan Yu. Tyukin
2021	J	`jnl`	High-Dimensional Separability for One- and Few-Shot Learning. Entropy Alexander N. Gorban, Bogdan Grechuk, Evgeny M. Mirkes, Sergey V. Stasenko, Ivan Yu. Tyukin
2021	J	`jnl`	High-dimensional separability for one- and few-shot learning. CoRR Alexander N. Gorban, Bogdan Grechuk, Evgeny M. Mirkes, Sergey V. Stasenko, Ivan Yu. Tyukin
2021	J	`jnl`	Learning from Scarce Information: Using Synthetic Data to Classify Roman Fine Ware Pottery. Entropy Santos J. Núñez Jareño, Daniël P. van Helden, Evgeny M. Mirkes, Ivan Yu. Tyukin, Penelope M. Allison
2021	J	`jnl`	Learning from scarce information: using synthetic data to classify Roman fine ware pottery. CoRR Santos J. Núñez Jareño, Daniël P. van Helden, Evgeny M. Mirkes, Ivan Yu. Tyukin, Penelope M. Allison
2021	J	`jnl`	The Feasibility and Inevitability of Stealth Attacks. CoRR Ivan Yu. Tyukin, Desmond J. Higham, Eliyas Woldegeorgis, Alexander N. Gorban
2020	J	`jnl`	General stochastic separation theorems with optimal bounds. CoRR Bogdan Grechuk, Alexander N. Gorban, Ivan Yu. Tyukin
2020	J	`jnl`	High-Dimensional Brain in a High-Dimensional World: Blessing of Dimensionality. CoRR Alexander N. Gorban, Valery A. Makarov, Ivan Yu. Tyukin
2020	J	`jnl`	High-Dimensional Brain in a High-Dimensional World: Blessing of Dimensionality. Entropy Alexander N. Gorban, Valery A. Makarov, Ivan Yu. Tyukin
2020	J	`jnl`	How Deep Should be the Depth of Convolutional Neural Networks: a Backyard Dog Case Study. Cogn. Comput. Alexander N. Gorban, Evgeny M. Mirkes, Ivan Yu. Tyukin
2020	B	`conf`	On Adversarial Examples and Stealth Attacks in Artificial Intelligence Systems. IJCNN Ivan Yu. Tyukin, Desmond J. Higham, Alexander N. Gorban
2020	J	`jnl`	On Adversarial Examples and Stealth Attacks in Artificial Intelligence Systems. CoRR Ivan Yu. Tyukin, Desmond J. Higham, Alexander N. Gorban
2019	J	`jnl`	Blessing of dimensionality at the edge. CoRR Ivan Yu. Tyukin, Alexander N. Gorban, Alistair A. McEwan, Sepehr Meshkinfamfard
2019	J	`jnl`	Fast construction of correcting ensembles for legacy Artificial Intelligence systems: Algorithms and a case study. Inf. Sci. Ivan Yu. Tyukin, Alexander N. Gorban, Stephen Green, Danil V. Prokhorov
2019	B	`conf`	Kernel Stochastic Separation Theorems and Separability Characterizations of Kernel Classifiers. IJCNN Ivan Yu. Tyukin, Alexander N. Gorban, Bogdan Grechuk, Stephen Green
2019	J	`jnl`	One-trial correction of legacy AI systems and stochastic separation theorems. Inf. Sci. Alexander N. Gorban, Richard Burton, Ilya V. Romanenko, Ivan Yu. Tyukin
2019	J	`jnl`	Symphony of high-dimensional brain. CoRR Alexander N. Gorban, Valeri A. Makarov, Ivan Yu. Tyukin
2018	J	`jnl`	Augmented Artificial Intelligence: a Conceptual Framework. CoRR Alexander N. Gorban, Bogdan Grechuk, Ivan Yu. Tyukin
2018	J	`jnl`	Blessing of dimensionality: mathematical foundations of the statistical physics of data. CoRR Alexander N. Gorban, Ivan Yu. Tyukin
2018	J	`jnl`	Correction of AI systems by linear discriminants: Probabilistic foundations. CoRR Alexander N. Gorban, A. Golubkov, Bogdan Grechuk, Evgeny M. Mirkes, Ivan Yu. Tyukin
2018	B	`conf`	Efficiency of Shallow Cascades for Improving Deep Learning AI Systems. IJCNN Ivan Yu. Tyukin, Alexander N. Gorban, Danil V. Prokhorov, Stephen Green
2018	J	`jnl`	Fast Construction of Correcting Ensembles for Legacy Artificial Intelligence Systems: Algorithms and a Case Study. CoRR Ivan Yu. Tyukin, Alexander N. Gorban, Stephen Green, Danil V. Prokhorov
2018	J	`jnl`	The unreasonable effectiveness of small neural ensembles in high-dimensional brain. CoRR Alexander N. Gorban, Valeri A. Makarov, Ivan Yu. Tyukin
2017	J	`jnl`	Knowledge Transfer Between Artificial Intelligence Systems. CoRR Ivan Yu. Tyukin, Alexander N. Gorban, Konstantin I. Sofeikov, Ilya V. Romanenko
2017	J	`jnl`	Stochastic Separation Theorems. CoRR Alexander N. Gorban, Ivan Yu. Tyukin
2017	J	`jnl`	Stochastic separation theorems. Neural Networks Alexander N. Gorban, Ivan Yu. Tyukin
2016	J	`jnl`	Approximation with random bases: Pro et Contra. Inf. Sci. Alexander N. Gorban, Ivan Yu. Tyukin, Danil V. Prokhorov, Konstantin I. Sofeikov
2016	J	`jnl`	The Blessing of Dimensionality: Separation Theorems in the Thermodynamic Limit. CoRR Alexander N. Gorban, Ivan Yu. Tyukin, Ilya V. Romanenko
2015	J	`jnl`	Approximation with Random Bases: Pro et Contra. CoRR Alexander N. Gorban, Ivan Yu. Tyukin, Danil V. Prokhorov, Konstantin I. Sofeikov
2014	—	`conf`	Further results on Lyapunov-like conditions of forward invariance and boundedness for a class of unstable systems. CDC Alexander N. Gorban, Ivan Yu. Tyukin, Henk Nijmeijer
2014	C	`conf`	Scene analysis assisting for AWB using binary decision trees and average image metrics. ICCE Konstantin I. Sofeikov, Ilya V. Romanenko, Ivan Yu. Tyukin, Alexander N. Gorban
2009	J	`jnl`	Adaptive Observers and Parameter Estimation for a Class of Systems Nonlinear in the Parameters. CoRR Ivan Yu. Tyukin, Erik Steur, Henk Nijmeijer, Cees van Leeuwen
2000	—	`conf`	Adaptive control on manifolds with RBF neural networks. CDC Valeri A. Terekhov, Ivan Yu. Tyukin, Danil V. Prokhorov