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NIPS
2007
13 years 9 months ago
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Maryam Mahdaviani, Tanzeem Choudhury
IVC
2006
180views more  IVC 2006»
13 years 8 months ago
Active appearance models with occlusion
Active Appearance Models (AAMs) are generative parametric models that have been successfully used in the past to track faces in video. A variety of video applications are possible...
Ralph Gross, Iain Matthews, Simon Baker
PVLDB
2008
94views more  PVLDB 2008»
13 years 7 months ago
Dynamic active probing of helpdesk databases
Helpdesk databases are used to store past interactions between customers and companies to improve customer service quality. One common scenario of using helpdesk database is to fi...
Shenghuo Zhu, Tao Li, Zhiyuan Chen, Dingding Wang,...
MICCAI
2010
Springer
13 years 6 months ago
Detecting Brain Activation in fMRI Using Group Random Walker
Due to the complex noise structure of functional magnetic resonance imaging (fMRI) data, methods that rely on information within a single subject often results in unsatisfactory fu...
Bernard Ng, Ghassan Hamarneh, Rafeef Abugharbieh
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 5 months ago
Active Learning from Multiple Noisy Labelers with Varied Costs
In active learning, where a learning algorithm has to purchase the labels of its training examples, it is often assumed that there is only one labeler available to label examples, ...
Yaling Zheng, Stephen D. Scott, Kun Deng