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» Learning Functions from Imperfect Positive Data
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ICML
2008
IEEE
14 years 11 months ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye
SIGKDD
2002
232views more  SIGKDD 2002»
13 years 9 months ago
The True Lift Model - A Novel Data Mining Approach to Response Modeling in Database Marketing
In database marketing, data mining has been used extensively to find the optimal customer targets so as to maximize return on investment. In particular, using marketing campaign d...
Victor S. Y. Lo
IJCNN
2007
IEEE
14 years 4 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
GI
2008
Springer
13 years 11 months ago
A Novel Conceptual Model for Accessing Distributed Data and Applications, as well as Devices
: As data and services are increasingly distributed in the network, rather than stored in a fixed location, one can imagine a scenario in which the Personal Computer, intended as a...
Lucia Terrenghi, Thomas Lang
ESANN
2004
13 years 11 months ago
Dimensionality reduction and classification using the distribution mapping exponent
: Probability distribution mapping function, which maps multivariate data distribution to the function of one variable, is introduced. Distributionmapping exponent (DME) is somethi...
Marcel Jirina