Bayesian Online Learning of the Hazard Rate in Change-Point Problems

@article{Wilson2010BayesianOL,
  title={Bayesian Online Learning of the Hazard Rate in Change-Point Problems},
  author={Robert C. Wilson and Matthew R. Nassar and Joshua I. Gold},
  journal={Neural Computation},
  year={2010},
  volume={22},
  pages={2452-2476}
}
Change-point models are generative models of time-varying data in which the underlying generative parameters undergo discontinuous changes at different points in time known as change points. Change-points often represent important events in the underlying processes, like a change in brain state reflected in EEG data or a change in the value of a company reflected in its stock price. However, change-points can be difficult to identify in noisy data streams. Previous attempts to identify change… CONTINUE READING