Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
The Modular Architecture for Bootstrapped Learning Experiments (MABLE) is a system that is being developed to allow humans to teach computers in the most natural manner possible: ...
Roger Mailler, Daniel Bryce, Jiaying Shen, Ciaran ...
While there is a lot of empirical evidence showing that traditional rule learning approaches work well in practice, it is nearly impossible to derive analytical results about thei...
Abstract. Capturing regularities in high-dimensional data is an important problem in machine learning and signal processing. Here we present a statistical model that learns a nonli...