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CVPR
2007
IEEE
16 years 7 months ago
Integrating Global and Local Structures: A Least Squares Framework for Dimensionality Reduction
Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...
Jianhui Chen, Jieping Ye, Qi Li
ICIP
2006
IEEE
16 years 6 months ago
Unsupervised Image Layout Extraction
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
David Liu, Datong Chen, Tsuhan Chen
134
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ICML
2006
IEEE
16 years 5 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
IEEEPACT
2009
IEEE
15 years 11 months ago
Interprocedural Load Elimination for Dynamic Optimization of Parallel Programs
Abstract—Load elimination is a classical compiler transformation that is increasing in importance for multi-core and many-core architectures. The effect of the transformation is ...
Rajkishore Barik, Vivek Sarkar
MMB
2004
Springer
102views Communications» more  MMB 2004»
15 years 10 months ago
Improving the Timeliness of Rate Measurements
Rate measurements are required for many purposes, e.g. for system analysis and modelling or for live systems that react to measurements. For off-line measurement all data is avail...
Rüdiger Martin, Michael Menth