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STOC
1993
ACM
141views Algorithms» more  STOC 1993»
15 years 6 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
ICCV
2007
IEEE
16 years 4 months ago
Learning Auto-Structured Regressor from Uncertain Nonnegative Labels
In this paper, we take the human age and pose estimation problems as examples to study automatic designing regressor from training samples with uncertain nonnegative labels. First...
Shuicheng Yan, Huan Wang, Xiaoou Tang, Thomas S. H...
CVPR
2012
IEEE
13 years 4 months ago
A learning based deformable template matching method for automatic rib centerline extraction and labeling in CT images
The automatic extraction and labeling of the rib centerlines is a useful yet challenging task in many clinical applications. In this paper, we propose a new approach integrating r...
Dijia Wu, David Liu, Zoltan Puskas, Chao Lu, Andre...
106
Voted
CVPR
2005
IEEE
16 years 4 months ago
Joint Nonparametric Alignment for Analyzing Spatial Gene Expression Patterns in Drosophila Imaginal Discs
To compare spatial patterns of gene expression, one must analyze a large number of images as current methods are only able to measure a small number of genes at a time. Bringing i...
Parvez Ahammad, Cyrus L. Harmon, Ann Hammonds, Sha...
111
Voted
ICML
1999
IEEE
16 years 2 months ago
Making Better Use of Global Discretization
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
Eibe Frank, Ian H. Witten