In this paper, we develop a new method for recovering and smoothing fields of surface normals in shape-fromshading. We show how transform the problem of recovering surface normals...
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
We describe a statistical approach to software debugging in the presence of multiple bugs. Due to sparse sampling issues and complex interaction between program predicates, many g...
Alice X. Zheng, Michael I. Jordan, Ben Liblit, May...
Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...