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» A Boosting Approach to Multiple Instance Learning
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ICCV
2009
IEEE
15 years 20 days ago
Action Detection in Complex Scenes with Spatial and Temporal Ambiguities
In this paper, we investigate the detection of semantic human actions in complex scenes. Unlike conventional action recognition in well-controlled environments, action detection...
Yuxiao Hu, Liangliang Cao, Fengjun Lv, Shuicheng Y...
EVOW
2008
Springer
13 years 9 months ago
A Hybrid Random Subspace Classifier Fusion Approach for Protein Mass Spectra Classification
Classifier fusion strategies have shown great potential to enhance the performance of pattern recognition systems. There is an agreement among researchers in classifier combination...
Amin Assareh, Mohammad Hassan Moradi, L. Gwenn Vol...
ICML
2004
IEEE
14 years 8 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 5 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
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
14 years 2 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...