Sequence Classification Using Third-Order Moments
DOI10.1162/neco_a_01033zbMath1472.92043OpenAlexW2770123274WikidataQ44685468 ScholiaQ44685468MaRDI QIDQ5157115
Lars Kai Hansen, Rasmus Troelsgaard
Publication date: 12 October 2021
Published in: Neural Computation (Search for Journal in Brave)
Full work available at URL: https://orbit.dtu.dk/en/publications/3fd1e57e-c3ab-4b36-a1a7-21c37a4d9584
Applications of statistics to biology and medical sciences; meta analysis (62P10) Markov processes: estimation; hidden Markov models (62M05) Neural networks for/in biological studies, artificial life and related topics (92B20) Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.) (68Q17)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A spectral algorithm for learning hidden Markov models
- Eigenvalue bounds on convergence to stationarity for nonreversible Markov chains, with an application to the exclusion process
- Tensor decompositions for learning latent variable models
- A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
This page was built for publication: Sequence Classification Using Third-Order Moments