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ICML
2008
IEEE
16 years 6 months ago
Graph transduction via alternating minimization
Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
Jun Wang, Tony Jebara, Shih-Fu Chang
CVPR
2008
IEEE
16 years 8 months ago
Spectral methods for semi-supervised manifold learning
Given a finite number of data points sampled from a low-dimensional manifold embedded in a high dimensional space together with the parameter vectors for a subset of the data poin...
Zhenyue Zhang, Hongyuan Zha, Min Zhang
CIARP
2007
Springer
16 years 8 days ago
Learning in Computer Vision: Some Thoughts
Abstract. It is argued that the ability to generalise is the most important characteristic of learning and that generalisation may be achieved only if pattern recognition systems l...
Maria Petrou
CVPR
2010
IEEE
15 years 8 months ago
Learning 3D Shape from a Single Facial Image via Non-linear Manifold Embedding and Alignment
The 3D reconstruction of a face from a single frontal image is an ill-posed problem. This is further accentuated when the face image is captured under different poses and/or compl...
Xianwang Wang, Ruigang Yang
NN
2006
Springer
114views Neural Networks» more  NN 2006»
15 years 6 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek