Research map / Probabilistic and scientific modeling / Variational and generative sampling
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace parametric/binned emissions with nonparametric spectral algorithm (NP-SpecHMM, KDE + Chebyshev continuous SVD) | HMM with nonparametric emissions · Internet Traffic, Laser Gen, Patient Sleep real datasets | mean prediction error (lower better) | Mixed |
| Use NP-SpecHMM instead of Gaussian-mixture EM HMM | Internet Traffic · Internet Traffic | mean prediction error: 0.143 -> 0.016 | Helped |
| Use NP-SpecHMM instead of binning with discrete spectral algorithm | Laser Gen · Laser Gen | mean prediction error: 0.31 -> 0.15 | Helped |
| Use NP-HSE instead of NP-SpecHMM on Patient Sleep | Patient Sleep · Patient Sleep | mean prediction error: 0.197 vs 0.225 (NP-SpecHMM worse) | Hurt |
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