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139
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PAMI
2008
162views more  PAMI 2008»
15 years 2 months ago
Dimensionality Reduction of Clustered Data Sets
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
Guido Sanguinetti
ICML
2007
IEEE
16 years 3 months ago
Adaptive dimension reduction using discriminant analysis and K-means clustering
We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...
Chris H. Q. Ding, Tao Li
119
Voted
ISLPED
2005
ACM
111views Hardware» more  ISLPED 2005»
15 years 8 months ago
Energy reduction in multiprocessor systems using transactional memory
The emphasis in microprocessor design has shifted from high performance, to a combination of high performance and low power. Until recently, this trend was mostly true for uniproc...
Tali Moreshet, R. Iris Bahar, Maurice Herlihy
DFT
2003
IEEE
106views VLSI» more  DFT 2003»
15 years 8 months ago
Techniques for Transient Fault Sensitivity Analysis and Reduction in VLSI Circuits
Transient faults in VLSI circuits could lead to disastrous consequences. With technology scaling, circuits are becoming increasingly vulnerable to transient faults. This papers pr...
Atul Maheshwari, Israel Koren, Wayne Burleson
112
Voted
BMVC
2001
15 years 5 months ago
Illumination technique for optical dynamic range compression and offset reduction
This paper presents a novel illumination technique for image processing in environmentswhich are characterized by large intensity fluctuations and hence a high optical dynamic ra...
C. Koch, S.-B. Park, Tim J. Ellis, A. Georgiadis