Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Maintaining data structure semantics of concurrent queues such as first-in first-out (FIFO) ordering requires expensive synchronization mechanisms which limit scalability. Howev...
The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse codingbased image super-resolution. Sparse coding is a typical unsupervi...
A novel approach for rendering time-varying data based on the Shear-Warp factorisation is presented. Reduction in storage space is achieved by detecting the changed areas within e...
Kostas Anagnostou, Tim J. Atherton, Andrew E. Wate...