We propose a learning algorithm for a variable memory length Markov process. Human communication, whether given as text, handwriting, or speech, has multi characteristic time scal...
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
In this paper we examine the ability to perform causal reasoning with equilibrium models. We explicate a postulate, which we term the Manipulation Postulate, that is required in o...
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Abstract: Cascade process, such as wastewater treatment plant, includes many nonlinear subsystems and many variables. When the number of sub-systems is big, the input-output relati...