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» Marginal Regression For Multitask Learning
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NAACL
2010
14 years 9 months ago
Painless Unsupervised Learning with Features
We show how features can easily be added to standard generative models for unsupervised learning, without requiring complex new training methods. In particular, each component mul...
Taylor Berg-Kirkpatrick, Alexandre Bouchard-C&ocir...
GBRPR
2007
Springer
15 years 3 months ago
Image Classification Using Marginalized Kernels for Graphs
We propose in this article an image classification technique based on kernel methods and graphs. Our work explores the possibility of applying marginalized kernels to image process...
Emanuel Aldea, Jamal Atif, Isabelle Bloch
ICCV
2007
IEEE
16 years 1 months ago
Spectral Regression for Efficient Regularized Subspace Learning
Subspace learning based face recognition methods have attracted considerable interests in recent years, including Principal Component Analysis (PCA), Linear Discriminant Analysis ...
Deng Cai, Xiaofei He, Jiawei Han
79
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NIPS
2007
15 years 1 months ago
A Risk Minimization Principle for a Class of Parzen Estimators
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
ML
2007
ACM
156views Machine Learning» more  ML 2007»
14 years 11 months ago
Active learning for logistic regression: an evaluation
Which active learning methods can we expect to yield good performance in learning binary and multi-category logistic regression classifiers? Addressing this question is a natural ...
Andrew I. Schein, Lyle H. Ungar