Both optimization and learning play important roles in a system for intelligent tasks. On one hand, we introduce three types of optimization tasks studied in the machine learning l...
We describe an approach for pipelining nested data collections in scientific workflows. Our approach logically delimits arbitrarily nested collections of data tokens using special...
As software becomes increasingly complex and difficult to analyze, it is more and more common for developers to use high-level, type-safe, object-oriented (OO) programming langua...
ibe an algorithm for proving termination of programs abstracted to systems of monotonicity constraints in the integer domain. Monotonicity constraints are a non-trivial extension ...
Michael Codish, Igor Gonopolskiy, Amir M. Ben-Amra...
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...