Abstract. Conditional Random Fields (CRFs) provide a powerful instrument for labeling sequences. So far, however, CRFs have only been considered for labeling sequences over flat al...
We have previously developed several algorithms which deal with different input sequence scenarios respectively. In this paper, another sequential algorithm for computing Longest ...
We investigate the degree sequences of scale-free random graphs. We obtain a formula for the limiting proportion of vertices with degree d, confirming non-rigorous arguments of Do...
Background: The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function un...
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...