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ML
2007
ACM
156views Machine Learning» more  ML 2007»
13 years 8 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
CIKM
2008
Springer
13 years 10 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
FGR
2008
IEEE
153views Biometrics» more  FGR 2008»
14 years 3 months ago
Facial image analysis using local feature adaptation prior to learning
Many facial image analysis methods rely on learningbased techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and...
Rogerio Feris, Ying-li Tian, Yun Zhai, Arun Hampap...
IJCNN
2000
IEEE
14 years 1 months ago
A Neural Support Vector Network Architecture with Adaptive Kernels
In the Support Vector Machines (SVM) framework, the positive-definite kernel can be seen as representing a fixed similarity measure between two patterns, and a discriminant func...
Pascal Vincent, Yoshua Bengio
CUZA
2002
129views more  CUZA 2002»
13 years 8 months ago
Ad Hoc Metacomputing with Compeer
Metacomputing allows the exploitation of geographically seperate, heterogenous networks and resources. Most metacomputers are feature rich and carry a long, complicated installati...
Keith Power, John P. Morrison