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ML
2002
ACM
167views Machine Learning» more  ML 2002»
13 years 5 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...
ESA
2004
Springer
128views Algorithms» more  ESA 2004»
13 years 10 months ago
Incremental Algorithms for Facility Location and k-Median
In the incremental versions of Facility Location and k-Median, the demand points arrive one at a time and the algorithm must maintain a good solution by either adding each new dema...
Dimitris Fotakis
ICML
2001
IEEE
14 years 6 months ago
Some Theoretical Aspects of Boosting in the Presence of Noisy Data
This is a survey of some theoretical results on boosting obtained from an analogous treatment of some regression and classi cation boosting algorithms. Some related papers include...
Wenxin Jiang
ACL
2008
13 years 6 months ago
Beyond Log-Linear Models: Boosted Minimum Error Rate Training for N-best Re-ranking
Current re-ranking algorithms for machine translation rely on log-linear models, which have the potential problem of underfitting the training data. We present BoostedMERT, a nove...
Kevin Duh, Katrin Kirchhoff
COLT
2001
Springer
13 years 10 months ago
Geometric Bounds for Generalization in Boosting
We consider geometric conditions on a labeled data set which guarantee that boosting algorithms work well when linear classifiers are used as weak learners. We start by providing ...
Shie Mannor, Ron Meir