Abstract--Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over...
Structural semantics are fundamental to understanding both natural and man-made objects from languages to buildings. They are manifested as repeated structures or patterns and are...
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Distributed coding at the hidden layer of a multi-layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically req...
Gail A. Carpenter, Boriana L. Milenova, Benjamin W...
We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to ano...