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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 10 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
SAC
2008
ACM
13 years 9 months ago
Local linear regression with adaptive orthogonal fitting for the wind power application
For short-term forecasting of wind generation, a necessary step is to model the function for the conversion of meteorological variables (mainly wind speed) to power production. Su...
Pierre Pinson, Henrik Aalborg Nielsen, Henrik Mads...
BMCBI
2011
13 years 5 months ago
Systematic error detection in experimental high-throughput screening
Background: High-throughput screening (HTS) is a key part of the drug discovery process during which thousands of chemical compounds are screened and their activity levels measure...
Plamen Dragiev, Robert Nadon, Vladimir Makarenkov
ICFEM
2000
Springer
14 years 1 months ago
Using Use Cases in Executable Z
Use Cases are a wide-spread informal method for specifying the requirements of a technical system in the early development phase. Z is a formal notation which aims to support, bes...
Wolfgang Grieskamp, Markus Lepper
NIPS
2003
13 years 11 months ago
Feature Selection in Clustering Problems
A novel approach to combining clustering and feature selection is presented. It implements a wrapper strategy for feature selection, in the sense that the features are directly se...
Volker Roth, Tilman Lange