Learning with Imprecise Classes, Rare Instances, and Complex Relationships
Srinath Ravindran · National Conference on Artificial Intelligence · 2011
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.