A survey on hyperdimensional computing aka vector symbolic architectures, part ii: Applications, cognitive models, and challenges
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 …
commonly known under the names Hyperdimensional Computing and Vector Symbolic …
A theoretical perspective on hyperdimensional computing
A Thomas, S Dasgupta, T Rosing - Journal of Artificial Intelligence Research, 2021 - jair.org
Hyperdimensional (HD) computing is a set of neurally inspired methods for obtaining
highdimensional, low-precision, distributed representations of data. These representations …
highdimensional, low-precision, distributed representations of data. These representations …
Graphd: Graph-based hyperdimensional memorization for brain-like cognitive learning
Memorization is an essential functionality that enables today's machine learning algorithms
to provide a high quality of learning and reasoning for each prediction. Memorization gives …
to provide a high quality of learning and reasoning for each prediction. Memorization gives …
Revisiting hyperdimensional learning for fpga and low-power architectures
Today's applications are using machine learning algorithms to analyze the data collected
from a swarm of devices on the Internet of Things (IoT). However, most existing learning …
from a swarm of devices on the Internet of Things (IoT). However, most existing learning …
Geniehd: Efficient dna pattern matching accelerator using hyperdimensional computing
DNA pattern matching is widely applied in many bioinformatics applications. The increasing
volume of the DNA data exacerbates the runtime and power consumption to discover DNA …
volume of the DNA data exacerbates the runtime and power consumption to discover DNA …
Learning from hypervectors: A survey on hypervector encoding
Hyperdimensional computing (HDC) is an emerging computing paradigm that imitates the
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …
Quanthd: A quantization framework for hyperdimensional computing
Brain-inspired hyperdimensional (HD) computing models cognition by exploiting properties
of high dimensional statistics-high-dimensional vectors, instead of working with numeric …
of high dimensional statistics-high-dimensional vectors, instead of working with numeric …
F5-hd: Fast flexible fpga-based framework for refreshing hyperdimensional computing
Hyperdimensional (HD) computing is a novel computational paradigm that emulates the
brain functionality in performing cognitive tasks. The underlying computation of HD involves …
brain functionality in performing cognitive tasks. The underlying computation of HD involves …
Memory-inspired spiking hyperdimensional network for robust online learning
Recently, brain-inspired computing models have shown great potential to outperform today's
deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiking …
deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiking …
Bric: Locality-based encoding for energy-efficient brain-inspired hyperdimensional computing
Brain-inspired Hyperdimensional (HD) computing is a new computing paradigm emulating
the neuron's activity in high-dimensional space. The first step in HD computing is to map …
the neuron's activity in high-dimensional space. The first step in HD computing is to map …