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» Complexity of Inference in Graphical Models
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PVLDB
2008
160views more  PVLDB 2008»
13 years 6 months ago
BayesStore: managing large, uncertain data repositories with probabilistic graphical models
Several real-world applications need to effectively manage and reason about large amounts of data that are inherently uncertain. For instance, pervasive computing applications mus...
Daisy Zhe Wang, Eirinaios Michelakis, Minos N. Gar...
PAMI
2010
174views more  PAMI 2010»
13 years 5 months ago
Image Segmentation with a Unified Graphical Model
—We propose a unified graphical model that can represent both the causal and noncausal relationships among random variables and apply it to the image segmentation problem. Specif...
Lei Zhang 0011, Qiang Ji
UAI
2008
13 years 8 months ago
Adaptive inference on general graphical models
Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform upd...
Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mett...
ICIP
2005
IEEE
14 years 8 months ago
Variable module graphs: a framework for inference and learning in modular vision systems
We present a novel and intuitive framework for building modular vision systems for complex tasks such as surveillance applications. Inspired by graphical models, especially factor...
Amit Sethi, Mandar Rahurkar, Thomas S. Huang
JMLR
2006
118views more  JMLR 2006»
13 years 6 months ago
Learning Factor Graphs in Polynomial Time and Sample Complexity
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
Pieter Abbeel, Daphne Koller, Andrew Y. Ng