Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Rather than painful, manual, static, per-connection optimization of TCP buffer sizes simply to achieve acceptable performance for distributed applications [8, 10], many researcher...
The growing disparity between processor and memory speeds has caused memory bandwidth to become the performance bottleneck for many applications. In particular, this performance ga...
Debugging the performance of parallel and distributed systems remains a difficult task despite the widespread use of middleware packages for automatic distribution, communication...
Geometry processing applications frequently rely on octree structures, since they provide simple and efficient hierarchies for discrete data. However, octrees do not guarantee dire...