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ICML
2009
IEEE
14 years 9 months ago
A least squares formulation for a class of generalized eigenvalue problems in machine learning
Many machine learning algorithms can be formulated as a generalized eigenvalue problem. One major limitation of such formulation is that the generalized eigenvalue problem is comp...
Liang Sun, Shuiwang Ji, Jieping Ye
TIP
2008
79views more  TIP 2008»
13 years 8 months ago
An Overview and Performance Evaluation of Classification-Based Least Squares Trained Filters
An overview of the classification-based least squares trained filters on picture quality improvement algorithms is presented. For each algorithm, the training process is unique and...
Ling Shao, Hui Zhang, Gerard de Haan
JMLR
2010
143views more  JMLR 2010»
13 years 3 months ago
Regularized Discriminant Analysis, Ridge Regression and Beyond
Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...
Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jor...
TIP
2010
155views more  TIP 2010»
13 years 7 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
TWC
2008
158views more  TWC 2008»
13 years 8 months ago
Solving Box-Constrained Integer Least Squares Problems
A box-constrained integer least squares problem (BILS) arises from several wireless communications applications. Solving a BILS problem usually has two stages: reduction (or prepro...
Xiao-Wen Chang, Qing Han