Extending DenseHMM with Continuous Emission

Author:

Balcer KlaudiaORCID,Lipinski PiotrORCID

Publisher

Springer Nature Singapore

Reference11 articles.

1. Boeker, M., Hammer, H.L., Riegler, M.A., Halvorsen, P., Jakobsen, P.: Prediction of schizophrenia from activity data using hidden Markov model parameters. Neural Comput. Appl. 35, 5619–5630 (2022)

2. Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Stat. Soc. Ser. B (Methodol.) 39, 1–38 (1977)

3. Harper, F.M., Konstan, J.A.: The MovieLens datasets: history and context. ACM Trans. Interact. Intell. Syst. 5, 19:1–19:19 (2016)

4. Hsiao, R., Tam, Y., Schultz, T.: Generalized Baum-Welch algorithm for discriminative training on large vocabulary continuous speech recognition system. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 3769–3772 (2009)

5. Huang, K., Fu, X., Sidiropoulos, N.D.: Learning hidden Markov models from pairwise co-occurrences with application to topic modeling. In: International Conference on Machine Learning, vol. 80, pp. 2073–2082 (2018)

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