82 citations · 96 across the 6 of their papers we have counts for
7 papers
Autonomous Learning with High-Dimensional Computing Architecture Similar to von Neumann's
Pentti Kanerva
We model human and animal learning by computing with high-dimensional vectors (H = 10,000 for example). The architecture resembles traditional (von Neumann) computing with numbers,…
Computing with Residue Numbers in High-Dimensional Representation
Christopher J. Kymn, Denis Kleyko, E. Paxon Frady +4
We introduce Residue Hyperdimensional Computing, a computing framework that unifies residue number systems with an algebra defined over random, high-dimensional vectors. We show ho…
Learning and generalization of compositional representations of visual scenes
E. Paxon Frady, Spencer Kent, Quinn Tran +3
Complex visual scenes that are composed of multiple objects, each with attributes, such as object name, location, pose, color, etc., are challenging to describe in order to train n…
Computing with Hypervectors for Efficient Speaker Identification
Ping-Chen Huang, Denis Kleyko, Jan M. Rabaey +2
We introduce a method to identify speakers by computing with high-dimensional random vectors. Its strengths are simplicity and speed. With only 1.02k active parameters and a 128-mi…
Vector Symbolic Architectures as a Computing Framework for Emerging Hardware
Denis Kleyko, Mike Davies, E. Paxon Frady +8
This article reviews recent progress in the development of the computing framework vector symbolic architectures (VSA) (also known as hyperdimensional computing). This framework is…
High-dimensional distributed semantic spaces for utterances
Jussi Karlgren, Pentti Kanerva
High-dimensional distributed semantic spaces have proven useful and effective for aggregating and processing visual, auditory, and lexical information for many tasks related to hum…
Language Recognition using Random Indexing
Aditya Joshi, Johan Halseth, Pentti Kanerva
Random Indexing is a simple implementation of Random Projections with a wide range of applications. It can solve a variety of problems with good accuracy without introducing much c…