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» Aggregation-based model reduction of a Hidden Markov Model
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EMNLP
2007
15 years 5 months ago
Bootstrapping Information Extraction from Field Books
We present two machine learning approaches to information extraction from semi-structured documents that can be used if no annotated training data are available, but there does ex...
Sander Canisius, Caroline Sporleder
ICDAR
2011
IEEE
14 years 3 months ago
HMM-Based Alignment of Inaccurate Transcriptions for Historical Documents
—For historical documents, available transcriptions typically are inaccurate when compared with the scanned document images. Not only the position of the words and sentences are ...
Andreas Fischer, Emanuel Indermühle, Volkmar ...
138
Voted
ICASSP
2011
IEEE
14 years 7 months ago
EM-style optimization of hidden conditional random fields for grapheme-to-phoneme conversion
We have recently proposed an EM-style algorithm to optimize log-linear models with hidden variables. In this paper, we use this algorithm to optimize a hidden conditional random ï...
Georg Heigold, Stefan Hahn, Patrick Lehnen, Herman...
EMNLP
2006
15 years 5 months ago
A Hybrid Markov/Semi-Markov Conditional Random Field for Sequence Segmentation
Markov order-1 conditional random fields (CRFs) and semi-Markov CRFs are two popular models for sequence segmentation and labeling. Both models have advantages in terms of the typ...
Galen Andrew
137
Voted
APPROX
2008
Springer
119views Algorithms» more  APPROX 2008»
15 years 6 months ago
The Complexity of Distinguishing Markov Random Fields
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
Andrej Bogdanov, Elchanan Mossel, Salil P. Vadhan