A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...
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Adaptive motion system helps robots achieve human-like dexterity with minimal data
Despite rapid robotic automation advancements, most systems struggle to adapt their pre-trained movements to dynamic ...
Researchers develop an adaptive motion system that allows robots to generate human-like movements with minimal data ...
We propose a nested Gaussian process (nGP) as a locally adaptive prior for Bayesian nonparametric regression. Specified through a set of stochastic differential equations (SDEs), the nGP imposes a ...
Motivated by Gaussian tests for a time series, we are led to investigate the asymptotic behavior of the residual empirical processes of stochastic regression models. These models cover the fixed ...
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