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» Classification of musical genre: a machine learning approach
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ICML
2008
IEEE
16 years 2 months ago
Extracting and composing robust features with denoising autoencoders
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to use...
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pi...
117
Voted
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
15 years 8 months ago
An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning
— The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. We are investigating the possibility of de...
Mary Qu Yang, Jack Y. Yang
CVPR
2005
IEEE
16 years 3 months ago
Machine Learning for Clinical Diagnosis from Functional Magnetic Resonance Imaging
Functional Magnetic Resonance Imaging (fMRI) has enabled scientists to look into the active human brain. FMRI provides a sequence of 3D brain images with intensities representing ...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, No...
117
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CLEF
2007
Springer
15 years 8 months ago
MIRACLE at ImageCLEFanot 2007: Machine Learning Experiments on Medical Image Annotation
This paper describes the participation of MIRACLE research consortium at the ImageCLEF Medical Image Annotation task of ImageCLEF 2007. Our areas of expertise do not include image...
Sara Lana-Serrano, Julio Villena-Román, Jos...
100
Voted
ICML
2004
IEEE
16 years 2 months ago
A MFoM learning approach to robust multiclass multi-label text categorization
We propose a multiclass (MC) classification approach to text categorization (TC). To fully take advantage of both positive and negative training examples, a maximal figure-of-meri...
Sheng Gao, Wen Wu, Chin-Hui Lee, Tat-Seng Chua