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ML
2010
ACM
193views Machine Learning» more  ML 2010»
14 years 4 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
89
Voted
ICPR
2008
IEEE
15 years 4 months ago
Semi-supervised marginal discriminant analysis based on QR decomposition
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Rui Xiao, Pengfei Shi
SAC
2004
ACM
15 years 3 months ago
A cost-oriented approach for infrastructural design
The selection of a cost-minimizing combination of hardware and network components that satisfy organizational requirements is a complex design problem with multiple degrees of fre...
Danilo Ardagna, Chiara Francalanci, Marco Trubian
CORR
2010
Springer
207views Education» more  CORR 2010»
14 years 9 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
PRL
2008
198views more  PRL 2008»
14 years 9 months ago
Pose estimation and tracking using multivariate regression
This paper presents an extension of the relevance vector machine (RVM) algorithm to multivariate regression. This allows the application to the task of estimating the pose of an a...
Arasanathan Thayananthan, Ramanan Navaratnam, Bj&o...