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» Automatic Ordering of Subgoals - A Machine Learning Approach
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CGF
2005
252views more  CGF 2005»
13 years 7 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
AI
2006
Springer
13 years 7 months ago
Discovering the linear writing order of a two-dimensional ancient hieroglyphic script
This paper demonstrates how machine learning methods can be applied to deal with a realworld decipherment problem where very little background knowledge is available. The goal is ...
Shou de Lin, Kevin Knight
MICRO
2009
IEEE
113views Hardware» more  MICRO 2009»
14 years 2 months ago
Portable compiler optimisation across embedded programs and microarchitectures using machine learning
Building an optimising compiler is a difficult and time consuming task which must be repeated for each generation of a microprocessor. As the underlying microarchitecture changes...
Christophe Dubach, Timothy M. Jones, Edwin V. Boni...
ICML
2002
IEEE
14 years 8 months ago
A New Statistical Approach to Personal Name Extraction
We propose a new statistical approach to extracting personal names from a corpus. One of the key points of our approach is that it can both automatically learn the characteristics...
Zheng Chen, Liu Wenyin, Feng Zhang
CVPR
2008
IEEE
14 years 9 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher