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ECCV
2010
Springer
13 years 5 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
CHI
2011
ACM
12 years 9 months ago
Starcraft from the stands: understanding the game spectator
Video games are primarily designed for the players. However, video game spectating is also a popular activity, boosted by the rise of online video sites and major gaming tournamen...
Gifford Cheung, Jeff Huang
CVPR
2006
IEEE
14 years 7 months ago
Applying Ensembles of Multilinear Classifiers in the Frequency Domain
Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning, pattern recognition and computer vision. Theoret...
Christian Bauckhage, Thomas Käster, John K. T...
KDD
2005
ACM
182views Data Mining» more  KDD 2005»
14 years 6 months ago
Making holistic schema matching robust: an ensemble approach
The Web has been rapidly "deepened" by myriad searchable databases online, where data are hidden behind query interfaces. As an essential task toward integrating these m...
Bin He, Kevin Chen-Chuan Chang
SOSP
2005
ACM
14 years 2 months ago
Hibernator: helping disk arrays sleep through the winter
Energy consumption has become an important issue in high-end data centers, and disk arrays are one of the largest energy consumers within them. Although several attempts have been...
Qingbo Zhu, Zhifeng Chen, Lin Tan, Yuanyuan Zhou, ...