Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
We have explored in this paper a framework to test in a quantitative manner the stability of different endmember extraction and spectral unmixing algorithms based on the concept o...
Fermin Ayuso, Javier Setoain, Manuel Prieto, Chris...
Many applications call for methods to enable automatic extraction of structured information from unstructured natural language text. Due to inherent challenges of natural language ...
Open Information Extraction extracts relations from text without requiring a pre-specified domain or vocabulary. While existing techniques have used only shallow syntactic featur...
Janara Christensen, Mausam, Stephen Soderland, Ore...
This paper describes issues related to integrating image analysis techniques into case-based reasoning. Although the approach is generic, a high-throughput protein crystallization...
Igor Jurisica, Phil Rogers, Janice I. Glasgow, Suz...