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JMLR
2006
150views more  JMLR 2006»
15 years 2 months ago
Building Support Vector Machines with Reduced Classifier Complexity
Support vector machines (SVMs), though accurate, are not preferred in applications requiring great classification speed, due to the number of support vectors being large. To overc...
S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCos...
102
Voted
SIAMSC
2008
117views more  SIAMSC 2008»
15 years 2 months ago
Adaptive, Fast, and Oblivious Convolution in Evolution Equations with Memory
To approximate convolutions which occur in evolution equations with memory terms, a variable-stepsize algorithm is presented for which advancing N steps requires only O(N log N) op...
María López-Fernández, Christ...
117
Voted
MICCAI
2010
Springer
15 years 14 days ago
Multi-Diffusion-Tensor Fitting via Spherical Deconvolution: A Unifying Framework
Abstract. In analyzing diffusion magnetic resonance imaging, multitensor models address the limitations of the single diffusion tensor in situations of partial voluming and fiber c...
Thomas Schultz, Carl-Fredrik Westin, Gordon L. Kin...
115
Voted
FSTTCS
2009
Springer
15 years 9 months ago
Iterative Methods in Combinatorial Optimization
We describe a simple iterative method for proving a variety of results in combinatorial optimization. It is inspired by Jain’s iterative rounding method (FOCS 1998) for designing...
R. Ravi
ICALP
2010
Springer
15 years 7 months ago
Network Design via Core Detouring for Problems without a Core
Some of the currently best-known approximation algorithms for network design are based on random sampling. One of the key steps of such algorithms is connecting a set of source nod...
Fabrizio Grandoni, Thomas Rothvoß