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CVPR
2006
IEEE
14 years 9 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
ISLPED
2007
ACM
109views Hardware» more  ISLPED 2007»
13 years 9 months ago
A multi-model power estimation engine for accuracy optimization
RTL power macromodeling is a mature research topic with a variety of equation and table-based approaches. Despite its maturity, macromodeling is not yet widely accepted as an indu...
Felipe Klein, Guido Araujo, Rodolfo Azevedo, Rober...
GIS
2006
ACM
14 years 8 months ago
Object localization based on directional information case of 2D vector data
If you were told that some object A was perfectly (or somewhat, or not at all) in some direction (e.g., west, above-right) of some reference object B, where in space would you loo...
Stelian Coros, JingBo Ni, Pascal Matsakis
FOCI
2007
IEEE
14 years 1 months ago
Almost All Learning Machines are Singular
— A learning machine is called singular if its Fisher information matrix is singular. Almost all learning machines used in information processing are singular, for example, layer...
Sumio Watanabe
KDD
2010
ACM
287views Data Mining» more  KDD 2010»
13 years 9 months ago
Designing efficient cascaded classifiers: tradeoff between accuracy and cost
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu