We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
We show that the mistake bound for predicting the nodes of an arbitrary weighted graph is characterized (up to logarithmic factors) by the cutsize of a random spanning tree of the...
Abstract—We consider the problem of jointly optimizing random access and subgraph selection in coded wireless packet networks. As opposed to the corresponding scheduling approach...
Maximilian Riemensberger, Michael Heindlmaier, And...
Random walk graph kernel has been used as an important tool for various data mining tasks including classification and similarity computation. Despite its usefulness, however, it...
Abstract. We present a method for automatically segmenting skin lesions by initializing the random walker algorithm with seed points whose properties, such as colour and texture, h...
Paul Wighton, Maryam Sadeghi, Tim K. Lee, M. St...