Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
We study a time series model that can be viewed as a decision tree with Markov temporal structure. The model is intractable for exact calculations, thus we utilize variational app...
Michael I. Jordan, Zoubin Ghahramani, Lawrence K. ...
Sequencing of peptides by tandem mass spectrometry has matured to the key technology for proteomics. Noise in the measurement process strongly favors statistical models like NovoHM...
Hansruedi Peter, Bernd Fischer, Joachim M. Buhmann
We investigate a family of inference problems on Markov models, where many sample paths are drawn from a Markov chain and partial information is revealed to an observer who attemp...
Daniel Sheldon, M. A. Saleh Elmohamed, Dexter Koze...