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» Generalization Bounds for Learning Kernels
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FOCS
2010
IEEE
13 years 5 months ago
Boosting and Differential Privacy
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Cynthia Dwork, Guy N. Rothblum, Salil P. Vadhan
ESANN
2004
13 years 8 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
DAGM
2010
Springer
13 years 8 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen
PPOPP
2010
ACM
14 years 4 months ago
Scaling LAPACK panel operations using parallel cache assignment
In LAPACK many matrix operations are cast as block algorithms which iteratively process a panel using an unblocked algorithm and then update a remainder matrix using the high perf...
Anthony M. Castaldo, R. Clint Whaley
COMPGEOM
2008
ACM
13 years 9 months ago
Robust construction of the three-dimensional flow complex
The Delaunay triangulation and its dual the Voronoi diagram are ubiquitous geometric complexes. From a topological standpoint, the connection has recently been made between these ...
Frédéric Cazals, Aditya G. Parameswa...