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ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 7 months ago
Active Learning from Multiple Noisy Labelers with Varied Costs
In active learning, where a learning algorithm has to purchase the labels of its training examples, it is often assumed that there is only one labeler available to label examples, ...
Yaling Zheng, Stephen D. Scott, Kun Deng
COMPSAC
2002
IEEE
14 years 3 months ago
Evaluating Software Maintenance Cost Using Functional Redundancy Metrics
a Abstract— Source code copying for reuse (code cloning) is often observed in software implementations. Such code cloning causes difficulty when software functionalities are mod...
Takeo Imai, Yoshio Kataoka, Tetsuji Fukaya
AAAI
2010
13 years 11 months ago
Cost-Sensitive Semi-Supervised Support Vector Machine
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
ICCV
2007
IEEE
13 years 11 months ago
COST: An Approach for Camera Selection and Multi-Object Inference Ordering in Dynamic Scenes
Development of multiple camera based vision systems for analysis of dynamic objects such as humans is challenging due to occlusions and similarity in the appearance of a person wi...
Abhinav Gupta, Anurag Mittal, Larry S. Davis
JMLR
2006
134views more  JMLR 2006»
13 years 10 months ago
Considering Cost Asymmetry in Learning Classifiers
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
Francis R. Bach, David Heckerman, Eric Horvitz