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» Document Summarization Using Conditional Random Fields
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SIGIR
2009
ACM
14 years 2 months ago
An improved markov random field model for supporting verbose queries
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
Matthew Lease
ICCV
2003
IEEE
14 years 9 months ago
Discriminative Random Fields: A Discriminative Framework for Contextual Interaction in Classification
In this work we present Discriminative Random Fields (DRFs), a discriminative framework for the classification of image regions by incorporating neighborhood interactions in the l...
Sanjiv Kumar, Martial Hebert
ECCV
2008
Springer
14 years 9 months ago
Sparse Long-Range Random Field and Its Application to Image Denoising
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Yunpeng Li, Daniel P. Huttenlocher
CVPR
2008
IEEE
14 years 9 months ago
Selective hidden random fields: Exploiting domain-specific saliency for event classification
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
Vidit Jain, Amit Singhal, Jiebo Luo
COLING
2010
13 years 2 months ago
TimeML Events Recognition and Classification: Learning CRF Models with Semantic Roles
This paper analyzes the contribution of semantic roles to TimeML event recognition and classification. For that purpose, an approach using conditional random fields with a variety...
Hector Llorens, Estela Saquete, Borja Navarro-Colo...