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PAMI
2008
391views more  PAMI 2008»
13 years 7 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha
SIAMSC
2008
198views more  SIAMSC 2008»
13 years 7 months ago
Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
T. Bui-Thanh, Karen Willcox, Omar Ghattas
CN
2002
77views more  CN 2002»
13 years 7 months ago
MATE: multipath adaptive traffic engineering
Destination-based forwarding in traditional IP routers has not been able to take full advantage of multiple paths that frequently exist in Internet Service Provider Networks. As a...
Anwar Elwalid, Cheng Jin, Steven H. Low, Indra Wid...
IGARSS
2009
13 years 4 months ago
Unmixing Sparse Hyperspectral Mixtures
Finding an accurate sparse approximation of a spectral vector described by a linear model, when there is available a library of possible constituent signals (called endmembers or ...
Marian-Daniel Iordache, José M. Bioucas-Dia...
BMCBI
2005
158views more  BMCBI 2005»
13 years 7 months ago
Automated generation of heuristics for biological sequence comparison
Background: Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. ...
Guy St. C. Slater, Ewan Birney