no code implementations • 12 Nov 2021 • Denis Kleyko, Dmitri A. Rachkovskij, Evgeny Osipov, Abbas Rahimi
This is Part II of the two-part comprehensive survey devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA).
no code implementations • 11 Nov 2021 • Denis Kleyko, Dmitri A. Rachkovskij, Evgeny Osipov, Abbas Rahimi
Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and vector distributed representations.
1 code implementation • 15 Oct 2021 • Evgeny Osipov, Sachin Kahawala, Dilantha Haputhanthri, Thimal Kempitiya, Daswin De Silva, Damminda Alahakoon, Denis Kleyko
Motivated by recent innovations in biologically-inspired neuromorphic hardware, this article presents a novel unsupervised machine learning algorithm named Hyperseed that draws on the principles of Vector Symbolic Architectures (VSA) for fast learning of a topology preserving feature map of unlabelled data.
no code implementations • 17 Jun 2021 • Antonello Rosato, Massimo Panella, Evgeny Osipov, Denis Kleyko
A change of the prevalent supervised learning techniques is foreseeable in the near future: from the complex, computational expensive algorithms to more flexible and elementary training ones.
no code implementations • 9 Jun 2021 • Denis Kleyko, Mike Davies, E. Paxon Frady, Pentti Kanerva, Spencer J. Kent, Bruno A. Olshausen, Evgeny Osipov, Jan M. Rabaey, Dmitri A. Rachkovskij, Abbas Rahimi, Friedrich T. Sommer
We see them acting as a framework for computing with distributed representations that can play a role of an abstraction layer for emerging computing hardware.
no code implementations • 25 Mar 2020 • Denis Kleyko, Ross W. Gayler, Evgeny Osipov
This correspondence comments on the findings reported in a recent Science Robotics article by Mitrokhin et al. [1].
no code implementations • 3 Mar 2020 • Pedro Alonso, Kumar Shridhar, Denis Kleyko, Evgeny Osipov, Marcus Liwicki
The embedding achieved on par F1 scores while decreasing the time and memory requirements by several times compared to the conventional n-gram statistics, e. g., for one of the classifiers on a small dataset, the memory reduction was 6. 18 times; while train and test speed-ups were 4. 62 and 3. 84 times, respectively.
3 code implementations • 19 Sep 2019 • Denis Kleyko, Mansour Kheffache, E. Paxon Frady, Urban Wiklund, Evgeny Osipov
The deployment of machine learning algorithms on resource-constrained edge devices is an important challenge from both theoretical and applied points of view.
no code implementations • 1 Jun 2017 • Denis Kleyko, E. Paxon Frady, Mansour Kheffache, Evgeny Osipov
We propose an approximation of Echo State Networks (ESN) that can be efficiently implemented on digital hardware based on the mathematics of hyperdimensional computing.
1 code implementation • 10 May 2017 • Denis Kleyko, Abbas Rahimi, Ross W. Gayler, Evgeny Osipov
A Bloom filter is a simple data structure supporting membership queries on a set.
Data Structures and Algorithms
no code implementations • 15 Jan 2015 • Denis Kleyko, Evgeny Osipov, Alexander Senior, Asad I. Khan, Y. Ahmet Şekercioğlu
This article proposes the use of Vector Symbolic Architectures for implementing Hierarchical Graph Neuron, an architecture for memorizing patterns of generic sensor stimuli.