Learning with Imprecise Classes, Rare Instances, and Complex Relationships
Abstract
In applications including chemoinformatics, bioinfor- matics, information retrieval, text classification, com- puter vision and others, a variety of common issues have been identified involving frequency of occurrence, variation and similarities of instances, and lack of pre- cise class labels. These issues continue to be important hurdles in machine intelligence and my doctoral thesis focuses on developing robust machine learning models that address the same.
Cite
Text
Ravindran. "Learning with Imprecise Classes, Rare Instances, and Complex Relationships." AAAI Conference on Artificial Intelligence, 2011.Markdown
[Ravindran. "Learning with Imprecise Classes, Rare Instances, and Complex Relationships." AAAI Conference on Artificial Intelligence, 2011.](https://mlanthology.org/aaai/2011/ravindran2011aaai-learning/)BibTeX
@inproceedings{ravindran2011aaai-learning,
title = {{Learning with Imprecise Classes, Rare Instances, and Complex Relationships}},
author = {Ravindran, Srinath},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2011},
url = {https://mlanthology.org/aaai/2011/ravindran2011aaai-learning/}
}