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» Using Random Forests in the Structured Language Model
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WSC
2000
13 years 10 months ago
Input modeling using a computer algebra system
Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit ...
Diane L. Evans, Lawrence Leemis
JMLR
2008
230views more  JMLR 2008»
13 years 8 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
WCE
2007
13 years 9 months ago
Reliability of Fatigue Damaged Structure Using FORM, SORM and Fatigue Model
—The methodologies to calculate failure probability and to estimate the reliability of fatigue loaded structures are developed. The applicability of the methodologies is evaluate...
Ouk Sub Lee, Dong Hyeok Kim
ACL
1998
13 years 10 months ago
Exploiting Syntactic Structure for Language Modeling
The paper presents a language model that develops syntactic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance d...
Ciprian Chelba, Frederick Jelinek
BMCBI
2010
190views more  BMCBI 2010»
13 years 8 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...