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153
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ICML
2005
IEEE
16 years 4 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
131
Voted
ITICSE
2004
ACM
15 years 9 months ago
Generation as method for explorative learning in computer science education
The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advant...
Andreas Kerren
134
Voted
PC
2010
101views Management» more  PC 2010»
14 years 10 months ago
An efficient parallel implementation of the MSPAI preconditioner
We present an efficient implementation of the Modified SParse Approximate Inverse (MSPAI) preconditioner. MSPAI generalizes the class of preconditioners based on Frobenius norm mi...
Thomas Huckle, A. Kallischko, A. Roy, M. Sedlacek,...
146
Voted
AAAI
2008
15 years 6 months ago
Sparse Projections over Graph
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
Deng Cai, Xiaofei He, Jiawei Han
141
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CVPR
2007
IEEE
16 years 5 months ago
Face Recognition Using Kernel Ridge Regression
In this paper, we present novel ridge regression (RR) and kernel ridge regression (KRR) techniques for multivariate labels and apply the methods to the problem of face recognition...
Senjian An, Wanquan Liu, Svetha Venkatesh