Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
General-purpose ontologies (e.g. WordNet) are convenient, but they are not always scientifically valid. We draw on techniques from semantic class learning to improve the scientific...
In language learning, strong relationships between Gold-style models and query models have recently been observed: in some quite general setting Gold-style learners can be replaced...
Automatically acquiring control-knowledge for planning, as it is the case for Machine Learning in general, strongly depends on the training examples. In the case of planning, examp...
We consider history independent data structures as proposed for study by Naor and Teague [3]. In a history independent data structure, nothing can be learned from the memory repre...
Jason D. Hartline, Edwin S. Hong, Alexander E. Moh...