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ICASSP
2010
IEEE
13 years 10 months ago
Language recognition using deep-structured conditional random fields
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...
Dong Yu, Shizhen Wang, Zahi Karam, Li Deng
CORR
2006
Springer
76views Education» more  CORR 2006»
13 years 10 months ago
Inconsistent parameter estimation in Markov random fields: Benefits in the computation-limited setting
Consider the problem of joint parameter estimation and prediction in a Markov random field: i.e., the model parameters are estimated on the basis of an initial set of data, and th...
Martin J. Wainwright
JMLR
2008
159views more  JMLR 2008»
13 years 10 months ago
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Existing template-independent web data extraction approaches adopt highly ineffective decoupled strategies--attempting to do data record detection and attribute labeling in two se...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
PAMI
2010
396views more  PAMI 2010»
13 years 8 months ago
Self-Validated Labeling of Markov Random Fields for Image Segmentation
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...
Wei Feng, Jiaya Jia, Zhi-Qiang Liu
ACL
2010
13 years 8 months ago
Jointly Optimizing a Two-Step Conditional Random Field Model for Machine Transliteration and Its Fast Decoding Algorithm
This paper presents a joint optimization method of a two-step conditional random field (CRF) model for machine transliteration and a fast decoding algorithm for the proposed metho...
Dong Yang, Paul R. Dixon, Sadaoki Furui