A novel technique for maximum "a posteriori" (MAP) adaptation of maximum entropy (MaxEnt) and maximum entropy Markov models (MEMM) is presented. The technique is applied...
The increasing complexity of configurable software systems creates a need for more intelligent sampling mechanisms to detect and locate failure-inducing dependencies between confi...
Adam A. Porter, Myra B. Cohen, Sandro Fouché...
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Over the past ten years, face detection has been thoroughly studied in computer vision research for its interesting applications. However, all of the state-of-the-art statistical ...
We present a sampling strategy and rendering framework for intersectable models, whose surface is implicitly defined by a black box intersection test that provides the location a...