Partially Supervised Learning Using an EM‐Boosting Algorithm

By Y. Yasui, M. Pepe, Li Hsu, Bao-Ling Adam, Ziding Feng. 2004

19 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ata Kabán
2. Jakramate Bootkrajang
3. P. Shanti Sastry
4. Himanshu Kumar
5. Jacob Goldberger
6. Ehud Ben-Reuven

In Molecular Biology

1. Ata Kabán
2. Jakramate Bootkrajang
3. P. Shanti Sastry
4. Himanshu Kumar
5. Jacob Goldberger
6. Ehud Ben-Reuven

Citations in the corpus

• Learning kernel logistic regression in the presence of class label noise (2014, background): “The presence of class label noise inherent in training samples has been reported to deteriorate the performance of the existing classifiers in a broad range of classification problems including biomedical data analysis [20,30] and image classification [24,47].”
• Label-Noise Robust Logistic Regression and Its Applications (2012, background): “The presence of class label noise inherent in training samples has been reported to deteriorate the performance of the existing classifiers in a broad range of classification problems [12, 25, 21].”