Denis Kleyko
Orcid: 0000-0002-6032-6155
According to our database1,
Denis Kleyko
authored at least 70 papers
between 2012 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2023
Generalized Key-Value Memory to Flexibly Adjust Redundancy in Memory-Augmented Networks.
IEEE Trans. Neural Networks Learn. Syst., December, 2023
Neural Comput., July, 2023
IEEE Trans. Neural Networks Learn. Syst., May, 2023
Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures.
J. Mach. Learn. Res., 2023
A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges.
ACM Comput. Surv., 2023
A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformations.
ACM Comput. Surv., 2023
2022
IEEE Trans. Neural Networks Learn. Syst., 2022
IEEE Trans. Neural Networks Learn. Syst., 2022
Proc. IEEE, 2022
Proceedings of the NICE 2022: Neuro-Inspired Computational Elements Conference, 2022
Proceedings of the NICE 2022: Neuro-Inspired Computational Elements Conference, 2022
Few-shot Federated Learning in Randomized Neural Networks via Hyperdimensional Computing.
Proceedings of the International Joint Conference on Neural Networks, 2022
Recursive Binding for Similarity-Preserving Hypervector Representations of Sequences.
Proceedings of the International Joint Conference on Neural Networks, 2022
2021
IEEE Trans. Neural Networks Learn. Syst., 2021
CoRR, 2021
CoRR, 2021
On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks.
Proceedings of the Advances in Computational Intelligence, 2021
Hyperdimensional Computing for Efficient Distributed Classification with Randomized Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2021
Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing.
Proceedings of the International Joint Conference on Neural Networks, 2021
HyperEmbed: Tradeoffs Between Resources and Performance in NLP Tasks with Hyperdimensional Computing Enabled Embedding of n-gram Statistics.
Proceedings of the International Joint Conference on Neural Networks, 2021
2020
IEEE Trans. Ind. Informatics, 2020
Neural Comput. Appl., 2020
Commentaries on "Learning Sensorimotor Control with Neuromorphic Sensors: Toward Hyperdimensional Active Perception" [Science Robotics Vol 4 Issue 30 (2019) 1-10.
CoRR, 2020
Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing, 2020
2019
IEEE Commun. Lett., 2019
A Hyperdimensional Computing Framework for Analysis of Cardiorespiratory Synchronization During Paced Deep Breathing.
IEEE Access, 2019
Parameter Estimation for the Resulting Logical Channel Formed by Minimizing Channel Switching.
Autom. Remote. Control., 2019
Trajectory clustering of road traffic in urban environments using incremental machine learning in combination with hyperdimensional computing.
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019
Proceedings of the International Joint Conference on Neural Networks, 2019
Low-Power Classification using FPGA - An Approach based on Cellular Automata, Neural Networks, and Hyperdimensional Computing.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019
Distributed Representation of n-gram Statistics for Boosting Self-organizing Maps with Hyperdimensional Computing.
Proceedings of the Perspectives of System Informatics, 2019
2018
Vector Symbolic Architectures and their applications: Computing with random vectors in a hyperdimensional space.
PhD thesis, 2018
Classification and Recall With Binary Hyperdimensional Computing: Tradeoffs in Choice of Density and Mapping Characteristics.
IEEE Trans. Neural Networks Learn. Syst., 2018
Robust Methods for Automated Selection of Cardiac Signals After Blind Source Separation.
IEEE Trans. Biomed. Eng., 2018
Neural Comput., 2018
Hyperdimensional Computing in Industrial Systems: The Use-Case of Distributed Fault Isolation in a Power Plant.
IEEE Access, 2018
A Domain Knowledge-Based Solution for Human Activity Recognition: The UJA Dataset Analysis.
Proceedings of the 12th International Conference on Ubiquitous Computing and Ambient Intelligence, 2018
Vector-Based Analysis of the Similarity Between Breathing and Heart Rate During Paced Deep Breathing.
Proceedings of the Computing in Cardiology, 2018
Detection of Atrial Fibrillation From Short ECGs: Minimalistic Complexity Analysis for Feature-Based Classifiers.
Proceedings of the Computing in Cardiology, 2018
2017
IEEE Trans. Neural Networks Learn. Syst., 2017
IEEE Trans. Circuits Syst. I Regul. Pap., 2017
CoRR, 2017
Theory of the superposition principle for randomized connectionist representations in neural networks.
CoRR, 2017
Modality classification of medical images with distributed representations based on cellular automata reservoir computing.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
Associative synthesis of finite state automata model of a controlled object with hyperdimensional computing.
Proceedings of the IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, Beijing, China, October 29, 2017
Poster: Approximate Sensing with Vector Symbolic Architectures: The case of fault isolation in distributed automation systems.
Proceedings of the 2017 International Conference on Embedded Wireless Systems and Networks, 2017
2016
Vehicle classification using road side sensors and feature-free data smashing approach.
Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems, 2016
Sparse Coding of Cardiac Signals for Automated Component Selection after Blind Source Separation.
Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016
Proceedings of the 7th Annual International Conference on Biologically Inspired Cognitive Architectures, 2016
Recognizing Permuted Words with Vector Symbolic Architectures: A Cambridge Test for Machines.
Proceedings of the 7th Annual International Conference on Biologically Inspired Cognitive Architectures, 2016
2015
Performance Peculiarities of Viterbi Decoder in Mathworks Simulink, GNU Radio and Other Systems with Likewise Implementation.
CoRR, 2015
An Approach for Self-Adaptive Path Loss Modeling for Accurate Positioning in Underground Environments.
CoRR, 2015
CoRR, 2015
Comparison of Machine Learning Techniques for Vehicle Classification Using Road Side Sensors.
Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems, 2015
Proceedings of the 13th IEEE International Conference on Industrial Informatics, 2015
Proceedings of the 6th Annual International Conference on Biologically Inspired Cognitive Architectures, 2015
2014
Proceedings of the Multiple Access Communications - 7th International Workshop, 2014
On methodology of implementing distributed function block applications using TinyOS WSN nodes.
Proceedings of the 2014 IEEE Emerging Technology and Factory Automation, 2014
On Bidirectional Transitions between Localist and Distributed Representations: The Case of Common Substrings Search Using Vector Symbolic Architecture.
Proceedings of the 5th Annual International Conference on Biologically Inspired Cognitive Architectures, 2014
2012
Dependable MAC Layer Architecture Based on Holographic Data Representation Using Hyper-Dimensional Binary Spatter Codes.
Proceedings of the Multiple Access Communications - 5th International Workshop, 2012