Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
— Classic adaptive control methods for handling varying loads rely on an analytically derived model of the robot’s dynamics. However, in many situations, it is not feasible or ...
: This research develops, operationalizes, and empirically tests a model for explaining/predicting the satisfaction of customers with Internet-based services in the context of an o...
Abstract— We present an adaptive control approach combining forward kinematics model learning methods with the operational space control approach. This combination endows the rob...
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...