In recent years, the size of combinatorial applications and the need to produce high-quality solutions quickly have increased steadily, providing significant challenges for optim...
Separating machine printed text and handwriting from overlapping text is a challenging problem in the document analysis field and no reliable algorithms have been developed thus f...
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
Unpredictability in the running time of complete search procedures can often be explained by the phenomenon of "heavy-tailed cost distributions", meaning that at any tim...
We present MI-CRF, a conditional random field (CRF) model for multiple instance learning (MIL). MI-CRF models bags as nodes in a CRF with instances as their states. It combines di...