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NIPS
2004
15 years 5 months ago
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
Robert Jenssen, Deniz Erdogmus, José Carlos...
ICML
2010
IEEE
15 years 4 months ago
A Simple Algorithm for Nuclear Norm Regularized Problems
Optimization problems with a nuclear norm regularization, such as e.g. low norm matrix factorizations, have seen many applications recently. We propose a new approximation algorit...
Martin Jaggi, Marek Sulovský
CORR
2008
Springer
114views Education» more  CORR 2008»
15 years 3 months ago
Support Vector Machine Classification with Indefinite Kernels
In this paper, we propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a nonconvex loss function, our...
Ronny Luss, Alexandre d'Aspremont
ASAP
2011
IEEE
228views Hardware» more  ASAP 2011»
14 years 3 months ago
A high-performance, low-power linear algebra core
—Achieving high-performance while reducing power consumption is a key concern as technology scaling is reaching its limits. It is well-accepted that application-specific custom ...
Ardavan Pedram, Andreas Gerstlauer, Robert A. van ...
KDD
1995
ACM
109views Data Mining» more  KDD 1995»
15 years 7 months ago
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
Michael J. Pazzani