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AAAI
2004
11 years 8 months ago
Online Parallel Boosting
This paper presents a new boosting (arcing) algorithm called POCA, Parallel Online Continuous Arcing. Unlike traditional boosting algorithms (such as Arc-x4 and Adaboost), that co...
Jesse A. Reichler, Harlan D. Harris, Michael A. Sa...
COLT
2008
Springer
11 years 8 months ago
On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms
Boosting algorithms build highly accurate prediction mechanisms from a collection of lowaccuracy predictors. To do so, they employ the notion of weak-learnability. The starting po...
Shai Shalev-Shwartz, Yoram Singer
COLT
1998
Springer
11 years 10 months ago
Improved Boosting Algorithms using Confidence-Rated Predictions
Abstract. We describe several improvements to Freund and Schapire's AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each o...
Robert E. Schapire, Yoram Singer
CVPR
2010
IEEE
11 years 11 months ago
On the design of robust classifiers for computer vision
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
Hamed Masnadi-Shirazi, Nuno Vasconcelos, Vijay Mah...
ECCV
2010
Springer
11 years 12 months ago
Robust Multi-View Boosting with Priors
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
ISVC
2007
Springer
12 years 22 days ago
Boosting with Temporal Consistent Learners: An Application to Human Activity Recognition
We present a novel boosting algorithm where temporal consistency is addressed in a short-term way. Although temporal correlation of observed data may be an important cue for classi...
Pedro Canotilho Ribeiro, Plinio Moreno, José...
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