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TIT
2010
100views Education» more  TIT 2010»
13 years 2 months ago
Theoretical and empirical results for recovery from multiple measurements
The joint-sparse recovery problem aims to recover, from sets of compressed measurements, unknown sparse matrices with nonzero entries restricted to a subset of rows. This is an ex...
Ewout van den Berg, Michael P. Friedlander
ACL
2007
13 years 9 months ago
Boosting Statistical Machine Translation by Lemmatization and Linear Interpolation
Data sparseness is one of the factors that degrade statistical machine translation (SMT). Existing work has shown that using morphosyntactic information is an effective solution t...
Ruiqiang Zhang, Eiichiro Sumita
CONEXT
2008
ACM
13 years 9 months ago
Towards high performance virtual routers on commodity hardware
Modern commodity hardware architectures, with their multiple multi-core CPUs and high-speed system interconnects, exhibit tremendous power. In this paper, we study performance lim...
Norbert Egi, Adam Greenhalgh, Mark Handley, Micka&...
CVPR
1999
IEEE
14 years 9 months ago
Integrating Shape from Shading and Range Data Using Neural Networks
This paper presents a framework for integrating multiple sensory data, sparse range data and dense depth maps from shape from shading in order to improve the 3D reconstruction of ...
Mostafa G.-H. Mostafa, Sameh M. Yamany, Aly A. Far...
IJON
2008
116views more  IJON 2008»
13 years 7 months ago
Discovering speech phones using convolutive non-negative matrix factorisation with a sparseness constraint
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...
Paul D. O'Grady, Barak A. Pearlmutter