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» Adaptation to Drifting Concepts
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MCS
2010
Springer
14 years 2 months ago
Online Non-stationary Boosting
Abstract. Oza’s Online Boosting algorithm provides a version of AdaBoost which can be trained in an online way for stationary problems. One perspective is that this enables the p...
Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, M...
ICPR
2010
IEEE
14 years 1 months ago
Inverse Multiple Instance Learning for Classifier Grids
Abstract--Recently, classifier grids have shown to be a considerable alternative for object detection from static cameras. However, one drawback of such approaches is drifting if a...
Sabine Sternig, Peter M. Roth, Horst Bischof
ICRA
2010
IEEE
150views Robotics» more  ICRA 2010»
13 years 8 months ago
Balancing state-space coverage in planning with dynamics
— Sampling-based kinodynamic planners, such as the popular RRT algorithm, have been proposed as promising solutions to planning for systems with dynamics. Nevertheless, complex s...
Yanbo Li, Kostas E. Bekris
PAMI
2012
12 years 1 days ago
Scribble Tracker: A Matting-Based Approach for Robust Tracking
—Model updating is a critical problem in tracking. Inaccurate extraction of the foreground and background information in model adaptation would cause the model to drift and degra...
Jialue Fan, Xiaohui Shen, Ying Wu
ADC
2006
Springer
123views Database» more  ADC 2006»
14 years 3 months ago
Recency-based collaborative filtering
Collaborative filtering is regarded as one of the most promising recommendation algorithms. Traditional approaches for collaborative filtering do not take concept drift into acc...
Yi Ding, Xue Li, Maria E. Orlowska