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ICML
2004
IEEE
14 years 9 months ago
Leveraging the margin more carefully
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...
Nir Krause, Yoram Singer
IROS
2007
IEEE
101views Robotics» more  IROS 2007»
14 years 3 months ago
Optimizing image and camera trajectories in robot vision control using on-line boosting
— In this paper, we present a novel boosted robot vision control algorithm. The method utilizes on-line boosting to produce a strong vision-based robot control starting from two ...
A. H. Abdul Hafez, Enric Cervera, C. V. Jawahar
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
14 years 9 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
HIS
2004
13 years 10 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
COLT
2000
Springer
14 years 1 months ago
PAC Analogues of Perceptron and Winnow via Boosting the Margin
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Rocco A. Servedio