We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
In this paper, we show the feasibility of real-time flow monitoring with controllable accuracy in today’s IP networks. Our approach is based on Netflow and A-GAP. A-GAP is a prot...
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...
As the number of cores and threads in manycore compute accelerators such as Graphics Processing Units (GPU) increases, so does the importance of on-chip interconnection network des...