We recently proposed a method for HMM adaptation to noisy environments called Linear Spline Interpolation (LSI). LSI uses linear spline regression to model the relationship betwee...
We propose a low-overhead sampling infrastructure for gathering information from the executions experienced by a program’s user community. Several example applications illustrat...
Ben Liblit, Alexander Aiken, Alice X. Zheng, Micha...
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Testing is often performed frequently during development to ensure software reliability by catching regression errors quickly. However, stopping frequently to test also wastes tim...
We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...