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» On learning algorithm selection for classification
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KDD
2003
ACM
150views Data Mining» more  KDD 2003»
16 years 7 months ago
Learning relational probability trees
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...
ICCV
2009
IEEE
15 years 4 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
ICASSP
2010
IEEE
15 years 6 months ago
Leveraging evaluation metric-related training criteria for speech summarization
Many of the existing machine-learning approaches to speech summarization cast important sentence selection as a two-class classification problem and have shown empirical success f...
Shih-Hsiang Lin, Yu-Mei Chang, Jia-Wen Liu, Berlin...
ICIAR
2009
Springer
15 years 4 months ago
A Robust Modular Wavelet Network Based Symbol Classifier
This paper presents a robust automatic shape classifier using modular wavelet networks (MWNs). A shape descriptor is constructed based on a combination of global geometric features...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...
CVPR
2007
IEEE
16 years 8 months ago
Concurrent Multiple Instance Learning for Image Categorization
We propose a new multiple instance learning (MIL) algorithm to learn image categories. Unlike existing MIL algorithms, in which the individual instances in a bag are assumed to be...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Tao Mei, Jin...