393 search results - page 1 / 79 » On the Convergence of Boosting Procedures |
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
COLT
2010
Springer
13 years 2 months ago
2010
Springer
Abstract. We pose the problem of determining the rate of convergence at which AdaBoost minimizes exponential loss. Boosting is the problem of combining many "weak," high-...
AVBPA
2003
Springer
13 years 8 months ago
2003
Springer
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
COLT
2000
Springer
13 years 9 months ago
2000
Springer
Boosting algorithms like AdaBoost and Arc-GV are iterative strategies to minimize a constrained objective function, equivalent to Barrier algorithms. Based on this new understandi...
CORR
2011
Springer
12 years 8 months ago
2011
Springer
The AdaBoost algorithm was designed to combine many “weak” hypotheses that perform slightly better than random guessing into a “strong” hypothesis that has very low error....