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05/26/2023
Efficient Decoding of Compositional Structure in Holistic Representations
We investigate the task of retrieving information from compositional dis...
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12/07/2022
Efficient Optimization with Higher-Order Ising Machines
A prominent approach to solving combinatorial optimization problems on p...
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08/28/2022
Computing with Hypervectors for Efficient Speaker Identification
We introduce a method to identify speakers by computing with high-dimens...
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03/11/2022
Generalized Key-Value Memory to Flexibly Adjust Redundancy in Memory-Augmented Networks
Memory-augmented neural networks enhance a neural network with an extern...
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03/02/2022
Integer Factorization with Compositional Distributed Representations
In this paper, we present an approach to integer factorization using dis...
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01/27/2022
Recursive Binding for Similarity-Preserving Hypervector Representations of Sequences
Hyperdimensional computing (HDC), also known as vector symbolic architec...
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11/11/2021
A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformations
This two-part comprehensive survey is devoted to a computing framework m...
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10/15/2021
HyperSeed: Unsupervised Learning with Vector Symbolic Architectures
Motivated by recent innovations in biologically-inspired neuromorphic ha...
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09/08/2021
Computing on Functions Using Randomized Vector Representations
Vector space models for symbolic processing that encode symbols by rando...
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06/17/2021
On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks
A change of the prevalent supervised learning techniques is foreseeable ...
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06/17/2021
Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing
Machine learning algorithms deployed on edge devices must meet certain r...
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06/09/2021
Vector Symbolic Architectures as a Computing Framework for Nanoscale Hardware
This article reviews recent progress in the development of the computing...
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06/02/2021
Hyperdimensional Computing for Efficient Distributed Classification with Randomized Neural Networks
In the supervised learning domain, considering the recent prevalence of ...
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12/14/2020
Perceptron Theory for Predicting the Accuracy of Neural Networks
Many neural network models have been successful at classification proble...
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10/11/2020
End to End Binarized Neural Networks for Text Classification
Deep neural networks have demonstrated their superior performance in alm...
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10/07/2020
Cellular Automata Can Reduce Memory Requirements of Collective-State Computing
Various non-classical approaches of distributed information processing, ...
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09/14/2020
Variable Binding for Sparse Distributed Representations: Theory and Applications
Symbolic reasoning and neural networks are often considered incompatible...
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03/25/2020
Commentaries on "Learning Sensorimotor Control with Neuromorphic Sensors: Toward Hyperdimensional Active Perception" [Science Robotics Vol. 4 Issue 30 (2019) 1-10
This correspondence comments on the findings reported in a recent Scienc...
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03/03/2020
HyperEmbed: Tradeoffs Between Resources and Performance in NLP Tasks with Hyperdimensional Computing enabled Embedding of n-gram Statistics
Recent advances in Deep Learning have led to a significant performance i...
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09/19/2019
Density Encoding Enables Resource-Efficient Randomly Connected Neural Networks
The deployment of machine learning algorithms on resource-constrained ed...
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02/28/2018
A theory of sequence indexing and working memory in recurrent neural networks
To accommodate structured approaches of neural computation, we propose a...
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07/05/2017
Theory of the superposition principle for randomized connectionist representations in neural networks
To understand cognitive reasoning in the brain, it has been proposed tha...
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06/01/2017