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» Bagging in Computer Vision
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ICML
2005
IEEE
14 years 10 months ago
Experimental comparison between bagging and Monte Carlo ensemble classification
Properties of ensemble classification can be studied using the framework of Monte Carlo stochastic algorithms. Within this framework it is also possible to define a new ensemble c...
Roberto Esposito, Lorenza Saitta
IPPS
2010
IEEE
13 years 7 months ago
Varying bandwidth resource allocation problem with bag constraints
We consider the problem of scheduling jobs on a pool of machines. Each job requires multiple machines on which it executes in parallel. For each job, the input specifies release ti...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Yogi...
CVPR
2009
IEEE
15 years 5 months ago
Efficient Kernels for Identifying Unbounded-Order Spatial Features
Higher order spatial features, such as doublets or triplets have been used to incorporate spatial information into the bag-of-local-features model. Due to computational limits, ...
Yimeng Zhang (Carnegie Mellon University), Tsuhan ...
CVPR
2012
IEEE
12 years 7 days ago
Two-person interaction detection using body-pose features and multiple instance learning
Human activity recognition has potential to impact a wide range of applications from surveillance to human computer interfaces to content based video retrieval. Recently, the rapi...
Kiwon Yun, Jean Honorio, Debaleena Chattopadhyay, ...
ICDM
2005
IEEE
179views Data Mining» more  ICDM 2005»
14 years 3 months ago
Bagging with Adaptive Costs
Ensemble methods have proved to be highly effective in improving the performance of base learners under most circumstances. In this paper, we propose a new algorithm that combine...
Yi Zhang, W. Nick Street