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» Algorithms for Large, Sparse Network Alignment Problems
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ICDCS
2000
IEEE
14 years 3 days ago
Static and Adaptive Data Replication Algorithms for Fast Information Access in Large Distributed Systems
Creating replicas of frequently accessed objects across a read-intensive network can result in large bandwidth savings which, in turn, can lead to reduction in user response time....
Thanasis Loukopoulos, Ishfaq Ahmad
CVPR
2010
IEEE
14 years 3 months ago
Learning Shift-Invariant Sparse Representation of Actions
A central problem in the analysis of motion capture (Mo- Cap) data is how to decompose motion sequences into primitives. Ideally, a description in terms of primitives should fac...
Yi Li
ICMLA
2009
13 years 5 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
ICML
2004
IEEE
14 years 8 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
TMI
2011
127views more  TMI 2011»
13 years 2 months ago
Reconstruction of Large, Irregularly Sampled Multidimensional Images. A Tensor-Based Approach
Abstract—Many practical applications require the reconstruction of images from irregularly sampled data. The spline formalism offers an attractive framework for solving this prob...
Oleksii Vyacheslav Morozov, Michael Unser, Patrick...