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118
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PKDD
2007
Springer
193views Data Mining» more  PKDD 2007»
15 years 8 months ago
Learning Multi-dimensional Functions: Gas Turbine Engine Modeling
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...
Chris Drummond
106
Voted
NPL
2000
95views more  NPL 2000»
15 years 2 months ago
Bayesian Sampling and Ensemble Learning in Generative Topographic Mapping
Generative topographic mapping (GTM) is a statistical model to extract a hidden smooth manifold from data, like the self-organizing map (SOM). Although a deterministic search algo...
Akio Utsugi
141
Voted
ICCV
2007
IEEE
16 years 4 months ago
The Joint Manifold Model for Semi-supervised Multi-valued Regression
Many computer vision tasks may be expressed as the problem of learning a mapping between image space and a parameter space. For example, in human body pose estimation, recent rese...
Ramanan Navaratnam, Andrew W. Fitzgibbon, Roberto ...
111
Voted
SMC
2007
IEEE
127views Control Systems» more  SMC 2007»
15 years 9 months ago
Underwater environment reconstruction using stereo and inertial data
Abstract— The underwater environment presents many challenges for robotic sensing including highly variable lighting, the presence of dynamic objects, and the six degree of freed...
Andrew Hogue, Andrew German, Michael Jenkin
134
Voted
VIS
2007
IEEE
128views Visualization» more  VIS 2007»
16 years 3 months ago
Modeling Perceptual Dominance Among Visual Cues in Multilayered Icon-based Scientific Visualizations
ization method is an abstract function that transforms a scientific dataset into a visual representation to facilitate data exploration. In turn, a visualization display is the vis...
Daniel Acevedo, Jian Chen, David H. Laidlaw