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» Language model adaptation using Random Forests
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EMNLP
2009
13 years 5 months ago
First- and Second-Order Expectation Semirings with Applications to Minimum-Risk Training on Translation Forests
Many statistical translation models can be regarded as weighted logical deduction. Under this paradigm, we use weights from the expectation semiring (Eisner, 2002), to compute fir...
Zhifei Li, Jason Eisner
BMCBI
2005
157views more  BMCBI 2005»
13 years 7 months ago
Decision Forest Analysis of 61 Single Nucleotide Polymorphisms in a Case-Control Study of Esophageal Cancer; a novel method
Background: Systematic evaluation and study of single nucleotide polymorphisms (SNPs) made possible by high throughput genotyping technologies and bioinformatics promises to provi...
Qian Xie, Luke D. Ratnasinghe, Huixiao Hong, Roger...
CVPR
2010
IEEE
14 years 4 months ago
Segmentation of Building Facades Using Procedural Shape Priors
In this paper we propose a novel approach to the perceptual interpretation of building facades that combines shape grammars, supervised classification and random walks. Procedural...
Olivier Teboul, Loic Simon, Panagiotis Koutsouraki...
ACL
2012
11 years 10 months ago
Akamon: An Open Source Toolkit for Tree/Forest-Based Statistical Machine Translation
We describe Akamon, an open source toolkit for tree and forest-based statistical machine translation (Liu et al., 2006; Mi et al., 2008; Mi and Huang, 2008). Akamon implements all...
Xianchao Wu, Takuya Matsuzaki, Jun-ichi Tsujii
ICIP
2006
IEEE
14 years 1 months ago
Discontinuity-Adaptive De-Interlacing Scheme Using Markov Random Field Model
— In this paper, a de-interlacing algorithm to find the optimal deinterlaced results given accuracy-limited motion information is proposed. The de-interlacing process is formula...
Min Li, Truong Q. Nguyen