3 citations · 4 across the 4 of their papers we have counts for
4 papers
An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computing
Igor Nunes, Mike Heddes, Tony Givargis +1
Hyperdimensional Computing (HDC) is a computation framework based on properties of high-dimensional random spaces. It is particularly useful for machine learning in resource-constr…
Hyperdimensional Hashing: A Robust and Efficient Dynamic Hash Table
Mike Heddes, Igor Nunes, Tony Givargis +2
Most cloud services and distributed applications rely on hashing algorithms that allow dynamic scaling of a robust and efficient hash table. Examples include AWS, Google Cloud and…
GraphHD: Efficient graph classification using hyperdimensional computing
Igor Nunes, Mike Heddes, Tony Givargis +2
Hyperdimensional Computing (HDC) developed by Kanerva is a computational model for machine learning inspired by neuroscience. HDC exploits characteristics of biological neural syst…
A Contextual Hierarchical Graph Model for Generating Random Sequences of Objects with Application to Music Playlists
Igor de Oliveira Nunes, Gabriel Matos Cardoso Leite, Daniel Ratton Figueiredo
Recommending the right content in large scale multimedia streaming services is an important and challenging problem that has received much attention in the past decade. A key ingre…