We present an algorithm for partial order reduction in the context of a countable universe of deterministic actions, of which finitely many are enabled at any given state. This mea...
In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Application-specific instructions can significantly improve the performance, energy, and code size of configurable processors. A common approach used in the design of such instruc...
Raising seeds for biological experiments is prone to error; a careful experimenter will test in the lab to verify that plants are of the intended strain. Choosing a minimal set of...