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» Adaptive Learning from Evolving Data Streams
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108
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MCS
2010
Springer
15 years 5 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...
FOCS
2010
IEEE
14 years 10 months ago
Boosting and Differential Privacy
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Cynthia Dwork, Guy N. Rothblum, Salil P. Vadhan
CVPR
2008
IEEE
15 years 17 days ago
Tracking distributions with an overlap prior
Recent studies have shown that embedding similarity/dissimilarity measures between distributions in the variational level set framework can lead to effective object segmentation/t...
Ismail Ben Ayed, Shuo Li, Ian G. Ross
SIGIR
2009
ACM
15 years 7 months ago
CompositeMap: a novel framework for music similarity measure
With the continuing advances in data storage and communication technology, there has been an explosive growth of music information from different application domains. As an effe...
Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wa...
81
Voted
PERCOM
2009
ACM
16 years 29 days ago
High Accuracy Context Recovery using Clustering Mechanisms
This paper examines the recovery of user context in indoor environments with existing wireless infrastructures to enable assistive systems. We present a novel approach to the extra...
Dinh Q. Phung, Brett Adams, Kha Tran, Svetha Venka...