For complex tasks such as parse selection, the creation of labelled training sets can be extremely costly. Resource-efficient schemes for creating informative labelled material mu...
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
This paper presents a new programming language named SPARCL that has four major elements: it is a visual language, it is a logic programming language, it relies on sets to organiz...
This paper describes a proposal for a set of Parallel Basic Linear Algebra Subprograms PBLAS. The PBLAS are targeted at distributed vector-vector, matrix-vector and matrixmatrix...
Jaeyoung Choi, Jack Dongarra, Susan Ostrouchov, An...
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
Charles Kemp, Thomas L. Griffiths, Sean Stromsten,...