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» A Markov random field model for term dependencies
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PRDC
2006
IEEE
15 years 3 months ago
Detecting and Exploiting Symmetry in Discrete-state Markov Models
Dependable systems are usually designed with multiple instances of components or logical processes, and often possess symmetries that may be exploited in model-based evaluation. T...
W. Douglas Obal II, Michael G. McQuinn, William H....
ICIP
1998
IEEE
15 years 11 months ago
Reducing the Computational Complexity of a Map Post-Processing Algorithm for Video Sequences
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
Mark A. Robertson, Robert L. Stevenson
DAGM
2008
Springer
14 years 11 months ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr
UAI
2008
14 years 11 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller
ACL
2010
14 years 7 months ago
Identifying Non-Explicit Citing Sentences for Citation-Based Summarization
Identifying background (context) information in scientific articles can help scholars understand major contributions in their research area more easily. In this paper, we propose ...
Vahed Qazvinian, Dragomir R. Radev