Name
Abstract | ||
|---|---|---|
We present a new model for multivariate time-series classification, called the hidden-unit logistic model (HULM), that uses binary stochastic hidden units to model latent structure in the data. The hidden units are connected in a chain structure that models temporal dependencies in the data. Compared with the prior models for time-series classification such as the hidden conditional random field, ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TNNLS.2017.2651018 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Hidden Markov models,Data models,Time series analysis,Stochastic processes,Computational modeling,Mathematical model,Logistics | Conditional random field,Data modeling,Time series,Pattern recognition,Computer science,Multivariate statistics,Latent class model,Stochastic process,Facial expression,Artificial intelligence,Hidden Markov model,Machine learning | Journal |
Volume | Issue | ISSN |
29 | 4 | 2162-237X |
Citations | PageRank | References |
9 | 0.59 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| wenjie pei | 1 | 43 | 8.10 |
| Hamdi Dibeklioglu | 2 | 198 | 15.05 |
| David M. J. Tax | 3 | 2071 | 148.87 |
| van der maaten | 4 | 763 | 48.75 |