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IJCAI
2001
13 years 11 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
FMSD
2006
103views more  FMSD 2006»
13 years 10 months ago
Compositional SCC Analysis for Language Emptiness
We propose a refinement approach to language emptiness, which is based on the enumeration and the successive refinements of SCCs on over-approximations of the exact system. Our alg...
Chao Wang, Roderick Bloem, Gary D. Hachtel, Kavita...
ACL
2007
13 years 11 months ago
Forest Rescoring: Faster Decoding with Integrated Language Models
Efficient decoding has been a fundamental problem in machine translation, especially with an integrated language model which is essential for achieving good translation quality. ...
Liang Huang, David Chiang
EMNLP
2007
13 years 11 months ago
Unsupervised Part-of-Speech Acquisition for Resource-Scarce Languages
This paper proposes a new bootstrapping approach to unsupervised part-of-speech induction. In comparison to previous bootstrapping algorithms developed for this problem, our appro...
Sajib Dasgupta, Vincent Ng
ACL
1998
13 years 11 months ago
Japanese OCR Error Correction using Character Shape Similarity and Statistical Language Model
We present a novel OCR error correction method for languages without word delimiters that have a large character set, such as Japanese and Chinese. It consists of a statistical OC...
Masaaki Nagata