We present the results of using Hidden Markov Models (HMMs) for automatic segmentation and recognition of user motions. Previous work on recognition of user intent with man/machin...
C. Sean Hundtofte, Gregory D. Hager, Allison M. Ok...
In this paper we formulate the problem of grouping the states of a discrete Markov chain of arbitrary order simultaneously with deconvolving its transition probabilities. As the na...
In this work, novel symbolic step encodings of the transition relation for object based communicating state machines are presented. This class of systems is tailored to capture the...
A hybrid neuro-symbolic problem-solving model is presented in which the aim is to forecast parameters of a complex and dynamic environment in an unsupervised way. In situations in ...
As modern multi-tier systems are becoming increasingly large and complex, it becomes more difficult for system analysts to understand the overall behavior of the system, and diag...