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ICML
2007
IEEE
14 years 10 months ago
A transductive framework of distance metric learning by spectral dimensionality reduction
Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
Fuxin Li, Jian Yang, Jue Wang
SC
2005
ACM
14 years 2 months ago
How Well Can Simple Metrics Represent the Performance of HPC Applications?
In this paper, a systematic study of the effects of complexity of prediction methodology on its accuracy for a set of real applications on a variety of HPC systems is performed. R...
Laura Carrington, Michael Laurenzano, Allan Snavel...
IMR
2003
Springer
14 years 2 months ago
A Local Cell Quality Metric and Variational Grid Smoothing Algorithm
A local cell quality metric is introduced and used to construct a variational functional for a grid smoothing algorithm. A maximum principle is proved and the properties of the loc...
Larisa Branets, Graham F. Carey
ECSQARU
2001
Springer
14 years 1 months ago
An Empirical Investigation of the K2 Metric
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
Christian Borgelt, Rudolf Kruse
VLC
2002
93views more  VLC 2002»
13 years 8 months ago
Metrics for Graph Drawing Aesthetics
Graph layout algorithms typically conform to one or more aesthetic criteria (e.g. minimising the number of bends, maximising orthogonality). Determining the extent to which a grap...
Helen C. Purchase