Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
In this paper, we propose a technique based on genetic programming (GP) for meshfree solution of elliptic partial differential equations. We employ the least-squares collocation pr...
Grid applications often need to distribute large amounts of data efficiently from one cluster to multiple others (multicast). Existing methods usually arrange nodes in optimized t...
Deploying multiple supply voltages (multi-Vdds) on one chip is an important technique to reduce dynamic power consumption. In this work we present an optimality study for resource...
We propose a sensornet programming model based on declarative spatio-temporal constraints on events only, not sensors. Where previous approaches conflate events and sensors becaus...