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ML
2002
ACM
167views Machine Learning» more  ML 2002»
13 years 7 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...
UAI
2004
13 years 9 months ago
Bidding under Uncertainty: Theory and Experiments
This paper describes a study of agent bidding strategies, assuming combinatorial valuations for complementary and substitutable goods, in three auction environments: sequential au...
Amy R. Greenwald, Justin A. Boyan
CVPR
2010
IEEE
14 years 3 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
CORR
2010
Springer
84views Education» more  CORR 2010»
13 years 7 months ago
On the Security of Non-Linear HB (NLHB) Protocol Against Passive Attack
As a variant of the HB authentication protocol for RFID systems, which relies on the complexity of decoding linear codes against passive attacks, Madhavan et al. presented Non-Line...
Mohammad Reza Sohizadeh Abyaneh
ICPR
2008
IEEE
14 years 8 months ago
A method of feature selection using contribution ratio based on boosting
AdaBoost and support vector machines (SVM) algorithms are commonly used in the field of object recognition. As classifiers, their classification performance is sensitive to affect...
Masamitsu Tsuchiya, Hironobu Fujiyoshi