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JMLR
2008
230views more  JMLR 2008»
14 years 11 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...
ACL
2006
15 years 14 days ago
Minimum Risk Annealing for Training Log-Linear Models
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
David A. Smith, Jason Eisner
CORR
2008
Springer
127views Education» more  CORR 2008»
14 years 11 months ago
MAPEL: Achieving Global Optimality for a Non-convex Wireless Power Control Problem
Achieving weighted throughput maximization (WTM) through power control has been a long standing open problem in interference-limited wireless networks. The complicated coupling bet...
Liping Qian, Ying Jun Zhang, Jianwei Huang
BMCBI
2010
115views more  BMCBI 2010»
14 years 11 months ago
Multiconstrained gene clustering based on generalized projections
Background: Gene clustering for annotating gene functions is one of the fundamental issues in bioinformatics. The best clustering solution is often regularized by multiple constra...
Jia Zeng, Shanfeng Zhu, Alan Wee-Chung Liew, Hong ...
CVPR
2005
IEEE
16 years 1 months ago
Dense Photometric Stereo Using a Mirror Sphere and Graph Cut
We present a surprisingly simple system that allows for robust normal reconstruction by dense photometric stereo, in the presence of severe shadows, highlight, transparencies, com...
Tai-Pang Wu, Chi-Keung Tang