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CVPR
2007
IEEE
16 years 8 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
173
Voted
CE
2008
122views more  CE 2008»
15 years 6 months ago
Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques
The portability and immediate communication properties of mobile devices influence the learning processes in interacting with peers, accessing resources and transferring data. For...
G. D. Chen, C. K. Chang, C. Y. Wang
ML
2000
ACM
154views Machine Learning» more  ML 2000»
15 years 6 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
WEBI
2010
Springer
15 years 4 months ago
Incorporating Seasonality into Search Suggestions Derived from Intranet Query Logs
While much research has been performed on query logs collected for major Web search engines, query log analysis to enhance search on smaller and more focused collections has attrac...
Stephen Dignum, Udo Kruschwitz, Maria Fasli, Yunhy...
AI
2006
Springer
15 years 6 months ago
Robot introspection through learned hidden Markov models
In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behaviour...
Maria Fox, Malik Ghallab, Guillaume Infantes, Dere...