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SIGIR
2008
ACM
13 years 7 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
EWMF
2003
Springer
14 years 1 months ago
Greedy Recommending Is Not Always Optimal
Abstract. Recommender systems suggest objects to users. One form recommends documents or other objects to users searching information on a web site. A recommender system can be use...
Maarten van Someren, Vera Hollink, Stephan ten Hag...
PVLDB
2008
122views more  PVLDB 2008»
13 years 7 months ago
Exploiting shared correlations in probabilistic databases
There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources -from sensor data, experimental data, data fro...
Prithviraj Sen, Amol Deshpande, Lise Getoor
FTCGV
2011
122views more  FTCGV 2011»
12 years 11 months ago
Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
Sebastian Nowozin, Christoph H. Lampert
ISBI
2004
IEEE
14 years 8 months ago
Probabilistic ICA for fMRI
Independent Component Analysis is becoming a popular exploratory method for analysing complex data such as that from FMRI experiments. The application of such `model-free' me...
Christian Beckmann