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ICML
2007
IEEE
16 years 5 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
AAAI
2008
15 years 7 months ago
CRF-OPT: An Efficient High-Quality Conditional Random Field Solver
Conditional random field (CRF) is a popular graphical model for sequence labeling. The flexibility of CRF poses significant computational challenges for training. Using existing o...
Minmin Chen, Yixin Chen, Michael R. Brent
NIPS
2008
15 years 6 months ago
Global Ranking Using Continuous Conditional Random Fields
This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
CVPR
2011
IEEE
15 years 1 months ago
Learning Non-Local Range Markov Random Field for Image Restoration
In this paper, we design a novel MRF framework which is called Non-Local Range Markov Random Field (NLRMRF). The local spatial range of clique in traditional MRF is extended to th...
Sun Jian, Marshall Tappen
230
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ICCV
2011
IEEE
14 years 5 months ago
Conditional Random Fields for Multi-Camera Object Detection
We formulate a model for multi-class object detection in a multi-camera environment. From our knowledge, this is the first time that this problem is addressed taken into account ...
Xavier Boix, Gemma Roig, Horesh Ben Shitrit, Pasca...