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» Information Theory, Inference, and Learning Algorithms
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SCESM
2006
ACM
269views Algorithms» more  SCESM 2006»
14 years 1 months ago
Inferring operational requirements from scenarios and goal models using inductive learning
Goal orientation is an increasingly recognised Requirements Engineering paradigm. However, integration of goal modelling with operational models remains an open area for which the...
Dalal Alrajeh, Alessandra Russo, Sebastián ...
SIGIR
2008
ACM
13 years 7 months ago
Personalized active learning for collaborative filtering
Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most infor...
Abhay Harpale, Yiming Yang
ML
2008
ACM
13 years 7 months ago
A bias/variance decomposition for models using collective inference
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
AIRWEB
2007
Springer
14 years 2 months ago
Transductive Link Spam Detection
Web spam can significantly deteriorate the quality of search engines. Early web spamming techniques mainly manipulate page content. Since linkage information is widely used in we...
Dengyong Zhou, Chris Burges, Tao Tao
ECML
2006
Springer
13 years 11 months ago
Transductive Gaussian Process Regression with Automatic Model Selection
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Quoc V. Le, Alexander J. Smola, Thomas Gärtne...