Learning models for recognizing objects with few or no training examples is important, due to the intrinsic longtailed distribution of objects in the real world. In this paper, we...
ACL2 is the latest inception of the Boyer-Moore theorem prover, the 2005 recipient of the ACM Software System Award. In the hands of an expert, it feels like a finely tuned race ...
Peter C. Dillinger, Panagiotis Manolios, Daron Vro...
Over the past few years, some embedding methods have been proposed for feature extraction and dimensionality reduction in various machine learning and pattern classification tasks...
Random forests are one of the best performing methods for constructing ensembles. They derive their strength from two aspects: using random subsamples of the training data (as in b...
We report on an experiment to implement an autonomous creature situated in a two-dimensional world, that shows various learning and problem-solving capabilities, within the Societ...