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» Interval discriminant analysis using support vector machines
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ICML
2004
IEEE
16 years 2 months ago
Multi-task feature and kernel selection for SVMs
We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
Tony Jebara
RECOMB
2005
Springer
16 years 1 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
NN
2008
Springer
201views Neural Networks» more  NN 2008»
15 years 1 months ago
Learning representations for object classification using multi-stage optimal component analysis
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Yiming Wu, Xiuwen Liu, Washington Mio
AI
2011
Springer
14 years 5 months ago
Using a Heterogeneous Dataset for Emotion Analysis in Text
In this paper, we adopt a supervised machine learning approach to recognize six basic emotions (anger, disgust, fear, happiness, sadness and surprise) using a heterogeneous emotion...
Soumaya Chaffar, Diana Inkpen
JMLR
2011
148views more  JMLR 2011»
14 years 8 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara