This work addresses the need for stateful dataflow programs that can rapidly sift through huge, evolving data sets. These data-intensive applications perform complex multi-step c...
Dionysios Logothetis, Christopher Olston, Benjamin...
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
The identification of categories in image databases usually relies on clustering algorithms that only exploit the feature-based similarities between images. The addition of semant...
Complex and dynamic interaction behaviors in applications such as Virtual Reality (VR) systems are difficult to design and develop. Reasons for this include the complexity and lim...
Advances in networking technology have enabled network engineers to use sampled data from routers to estimate network flow volumes and track them over time. However, low sampling ...