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PAMI
2008
139views more  PAMI 2008»
15 years 4 months ago
A Fast Algorithm for Learning a Ranking Function from Large-Scale Data Sets
We consider the problem of learning a ranking function that maximizes a generalization of the Wilcoxon-Mann-Whitney statistic on the training data. Relying on an -accurate approxim...
Vikas C. Raykar, Ramani Duraiswami, Balaji Krishna...
CSDA
2004
105views more  CSDA 2004»
15 years 4 months ago
Computational aspects of algorithms for variable selection in the context of principal components
Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...
Jorge Cadima, J. Orestes Cerdeira, Manuel Minhoto
WADS
2009
Springer
226views Algorithms» more  WADS 2009»
15 years 11 months ago
Online Priority Steiner Tree Problems
Abstract. A central issue in the design of modern communication networks is the provision of Quality-of-Service (QoS) guarantees at the presence of heterogeneous users. For instanc...
Spyros Angelopoulos
WADS
2007
Springer
128views Algorithms» more  WADS 2007»
15 years 10 months ago
Approximate Range Searching: The Absolute Model
Range searching is a well known problem in the area of geometric data structures. We consider this problem in the context of approximation, where an approximation parameter ε >...
Guilherme Dias da Fonseca
ATAL
2008
Springer
15 years 6 months ago
Adaptive Kanerva-based function approximation for multi-agent systems
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...
Cheng Wu, Waleed Meleis