On-chip L1 and L2 caches represent a sizeable fraction of the total power consumption of microprocessors. In deep sub-micron technology, the subthreshold leakage power is becoming...
The architectural design of embedded systems is becoming increasingly idiosyncratic to meet varying constraints regarding energy consumption, code size, and execution time. Tradit...
Parser self-training is the technique of taking an existing parser, parsing extra data and then creating a second parser by treating the extra data as further training data. Here ...
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. In particular, r...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...