We propose regression modeling as an efficient approach for accurately predicting performance and power for various applications executing on any microprocessor configuration in a...
Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multi-extremal. This presents a significant challenge t...
We present an integrated approach to speech and natural language processing which uses a single parser to create training for a statistical speech recognition component and for in...
The problem of deciding the probability model equivalence of two PRISM programs is addressed. In the finite case this problem can be solved (albeit slowly) using techniques from a...
We demonstrate a new research approach to the problem of predicting the reading difficulty of a text passage, by recasting readability in terms of statistical language modeling. W...