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156
Voted
MM
2010
ACM
238views Multimedia» more  MM 2010»
15 years 3 months ago
Supervised manifold learning for image and video classification
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
Yang Liu, Yan Liu, Keith C. C. Chan
122
Voted
ICML
2003
IEEE
16 years 4 months ago
Kernel PLS-SVC for Linear and Nonlinear Classification
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
Roman Rosipal, Leonard J. Trejo, Bryan Matthews
107
Voted
CHI
2009
ACM
16 years 4 months ago
Using temporal patterns (t-patterns) to derive stress factors of routine tasks
We describe the use of a statistical technique called Tpattern analysis to derive and characterize the routineness of tasks. T-patterns provide significant advantages over traditi...
Oliver Brdiczka, Norman Makoto Su, Bo Begole
114
Voted
HPCA
2008
IEEE
16 years 4 months ago
Roughness of microarchitectural design topologies and its implications for optimization
Recent advances in statistical inference and machine learning close the divide between simulation and classical optimization, thereby enabling more rigorous and robust microarchit...
Benjamin C. Lee, David M. Brooks
117
Voted
ICCAD
2007
IEEE
175views Hardware» more  ICCAD 2007»
16 years 18 days ago
Compact modeling of variational waveforms
— In ultra-deep sub-micron technologies, modeling waveform shapes correctly is essential for accurate timing and noise analysis. Due to process and environmental variations, ther...
Vladimir Zolotov, Jinjun Xiong, Soroush Abbaspour,...