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UAI
2008
10 years 5 months ago
Inference for Multiplicative Models
The paper introduces a generalization for known probabilistic models such as log-linear and graphical models, called here multiplicative models. These models, that express probabi...
Ydo Wexler, Christopher Meek
AAAI
2007
10 years 6 months ago
Unscented Message Passing for Arbitrary Continuous Variables in Bayesian Networks
Since Bayesian network (BN) was introduced in the field of artificial intelligence in 1980s, a number of inference algorithms have been developed for probabilistic reasoning. Ho...
Wei Sun, Kuo-Chu Chang
SKG
2006
IEEE
10 years 10 months ago
Abox Inference for Large Scale OWL-Lite Data
Abox inference is an important part in OWL data management. When involving large scale of instance data, it can not be supported by existing inference engines. In this paper, we p...
Xiaofeng Wang, Jianbo Ou, Xiaofeng Meng, Yan Chen
EMMCVPR
2007
Springer
10 years 10 months ago
Bayesian Inference for Layer Representation with Mixed Markov Random Field
Abstract. This paper presents a Bayesian inference algorithm for image layer representation [26], 2.1D sketch [6], with mixed Markov random field. 2.1D sketch is an very important...
Ru-Xin Gao, Tianfu Wu, Song Chun Zhu, Nong Sang
HPDC
2007
IEEE
10 years 10 months ago
A fast topology inference: a building block for network-aware parallel processing
Adapting to the network is the key to achieving high performance for communication-intensive applications, including scientific computing, data intensive computing, and multicast...
Tatsuya Shirai, Hideo Saito, Kenjiro Taura
ICCV
2003
IEEE
11 years 6 months ago
Comparison of Graph Cuts with Belief Propagation for Stereo, using Identical MRF Parameters
Recent stereo algorithms have achieved impressive results by modelling the disparity image as a Markov Random Field (MRF). An important component of an MRF-based approach is the i...
Marshall F. Tappen, William T. Freeman
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