Abstract: Locally weighted learning (LWL) is a class of techniques from nonparametric statistics that provides useful representations and training algorithms for learning about com...
Stefan Schaal, Christopher G. Atkeson, Sethu Vijay...
We propose a low-overhead method for delay fault testing in high-speed asynchronous pipelines. The key features of our work are: (i) testing strategies can be administered using l...
The Kolmogorov–Smirnov test determines the consistency of empirical data with a particular probability distribution. Often, parameters in the distribution are unknown, and have ...
Tracking people using movie sequences is not straightforward because of the human body's articulation and the complexity of a person's movements. In this paper we show ho...
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...