BR-iHMM adds bounded-PIF robustness to online iHMMs via generalized Bayesian updates and two extra tuning parameters, cutting forecasting error by up to 67% on three real and synthetic streams.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
stat.ML 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Streaming HMM inference is cast as a constrained projection onto an S-path mixture in predictive space, producing a deterministic recursive beam algorithm with closed-form updates.
citing papers explorer
-
Doubly Outlier-Robust Online Infinite Hidden Markov Model
BR-iHMM adds bounded-PIF robustness to online iHMMs via generalized Bayesian updates and two extra tuning parameters, cutting forecasting error by up to 67% on three real and synthetic streams.
-
A Predictive View on Streaming Hidden Markov Models
Streaming HMM inference is cast as a constrained projection onto an S-path mixture in predictive space, producing a deterministic recursive beam algorithm with closed-form updates.