Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
This paper consists of two parts. The first part is the development of a datadriven Kalman filter for a non-uniformly sampled multirate (NUSM) system, including identification of ...
Abstract This paper describes a document recognition system for the modern neume based notation of Byzantine music. We propose algorithms for page segmentation, lyrics removal, syn...
Christoph Dalitz, Georgios K. Michalakis, Christin...
SMT solvers have traditionally been based on the DPLL(T) algorithm, where the driving force behind the procedure is a DPLL search over truth valuations. This traditional framework ...
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...