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» Learning from Multiple Annotators with Gaussian Processes
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ICASSP
2011
IEEE
12 years 10 months ago
Detection of anomalous events from unlabeled sensor data in smart building environments
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
Padmini Jaikumar, Aca Gacic, Burton Andrews, Micha...
ICDM
2010
IEEE
160views Data Mining» more  ICDM 2010»
13 years 4 months ago
A Privacy Preserving Framework for Gaussian Mixture Models
Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Madhusudana Shashanka
ICIP
2005
IEEE
14 years 8 months ago
A complementary SVMs-based image annotation system
A novel automatic image annotation system is proposed, which integrates two sets of SVMs (Support Vector Machines), namely the MIL-based (Multiple Instance Learning) and global-fe...
Yutao Han, Xiaojun Qi
IJCNN
2008
IEEE
14 years 1 months ago
A comparison of fuzzy ARTMAP and Gaussian ARTMAP neural networks for incremental learning
Abstract— Automatic pattern classifiers that allow for incremental learning can adapt internal class models efficiently in response to new information, without having to retrai...
Eric Granger, Jean-François Connolly, Rober...
MM
2004
ACM
170views Multimedia» more  MM 2004»
14 years 5 days ago
Effective automatic image annotation via a coherent language model and active learning
Image annotations allow users to access a large image database with textual queries. There have been several studies on automatic image annotation utilizing machine learning techn...
Rong Jin, Joyce Y. Chai, Luo Si