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» On the Optimality of the Dimensionality Reduction Method
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CVPR
2007
IEEE
16 years 8 months ago
Learning Kernel Expansions for Image Classification
Kernel machines (e.g. SVM, KLDA) have shown state-ofthe-art performance in several visual classification tasks. The classification performance of kernel machines greatly depends o...
Fernando De la Torre, Oriol Vinyals
ICPR
2004
IEEE
16 years 7 months ago
Nearest Neighbor Ensemble
Recent empirical work has shown that combining predictors can lead to significant reduction in generalization error. The individual predictors (weak learners) can be very simple, ...
Bojun Yan, Carlotta Domeniconi
ICML
2009
IEEE
16 years 7 months ago
Learning spectral graph transformations for link prediction
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Andreas Lommatzsch, Jérôme Kunegis
VLSID
2007
IEEE
120views VLSI» more  VLSID 2007»
16 years 6 months ago
Statistical Leakage and Timing Optimization for Submicron Process Variation
Leakage power is becoming a dominant contributor to the total power consumption and dual-Vth assignment is an efficient technique to decrease leakage power, for which effective de...
Yuanlin Lu, Vishwani D. Agrawal
ICIP
2007
IEEE
15 years 10 months ago
Unsupervised Nonlinear Manifold Learning
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...