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RegHD: Robust and Efficient Regression in Hyper-Dimensional Learning System
Time
Location
Event Type
Research Manuscript
Virtual Programs
Hosted in Virtual Platform
Keywords
AI/ML System Design
Topics
Design
DescriptionTo achieve real-time performance with high energy efficiency and robustness, we proposed RegHD, the first regression solution based on Hyperdimensional computing. RegHD redesigns a regression algorithm using strategies that more closely model the ultimate efficient learning machine: the human brain. RegHD creates two set of models: Input Model to cluster data points with high similarity, and Regression Model to generate a regression model for each clustered data. During prediction, RegHD computes the output value by the weighted accumulation of all regression models, considering the model confidence obtained during similarity search.