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JCP
2006
118views more  JCP 2006»
15 years 6 months ago
Learning a Classification-based Glioma Growth Model Using MRI Data
Gliomas are malignant brain tumors that grow by invading adjacent tissue. We propose and evaluate a 3D classification-based growth model, CDM, that predicts how a glioma will grow ...
Marianne Morris, Russell Greiner, Jörg Sander...
AIEDAM
1998
87views more  AIEDAM 1998»
15 years 6 months ago
Learning to set up numerical optimizations of engineering designs
Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the object...
Mark Schwabacher, Thomas Ellman, Haym Hirsh
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
15 years 5 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas
AAAI
2010
15 years 4 months ago
Non-I.I.D. Multi-Instance Dimensionality Reduction by Learning a Maximum Bag Margin Subspace
Multi-instance learning, as other machine learning tasks, also suffers from the curse of dimensionality. Although dimensionality reduction methods have been investigated for many ...
Wei Ping, Ye Xu, Kexin Ren, Chi-Hung Chi, Shen Fur...
CVPR
2009
IEEE
15 years 4 months ago
Learning IMED via shift-invariant transformation
The IMage Euclidean Distance (IMED) is a class of image metrics, in which the spatial relationship between pixels is taken into consideration. It was shown that calculating the IM...
Bing Sun, Jufu Feng, Liwei Wang