Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Background: Computational identification of blood-secretory proteins, especially proteins with differentially expressed genes in diseased tissues, can provide highly useful inform...
—At ICSE 2010, the Code Bubbles team from Brown University and the Code Canvas team from Microsoft Research presented similar ideas for new user experiences for an integrated dev...
Robert DeLine, Andrew Bragdon, Kael Rowan, Jens Ja...
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...