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» Active Learning with Model Selection in Linear Regression
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TSP
2010
13 years 3 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
JMLR
2011
148views more  JMLR 2011»
13 years 3 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
CIBCB
2005
IEEE
13 years 10 months ago
Neuro-fuzzy Prediction of Biological Activity and Rule Extraction for HIV-1 Protease Inhibitors
— A fuzzy neural network (FNN) and multiple linear regression (MLR) were used to predict biological activities of 26 newly designed HIV-1 protease potential inhibitory compounds....
Razvan Andonie, Levente Fabry-Asztalos, Catharine ...
AVSS
2008
IEEE
14 years 3 months ago
A Fast Linear Registration Framework for Multi-camera GIS Coordination
We propose a novel registration framework to map the field-of-coverage of pan-tilt cameras to a GIS (Geographic Information System) planar coordinate system. The camera’s fiel...
Karthik Sankaranarayanan, James W. Davis
SIGIR
2004
ACM
14 years 2 months ago
Learning to cluster web search results
Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't g...
Hua-Jun Zeng, Qi-Cai He, Zheng Chen, Wei-Ying Ma, ...