Approximate Distributed Spatiotemporal Topic Models for Multi-Robot Terrain Characterization
Unsupervised learning techniques, such as Bayesian topic models, are capable of discovering latent structure directly from raw data. These unsupervised models can endow robots with the ability to learn from their observations without human supervision, and then use the learned models for tasks such...
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| Materialtyp: | Artikel |
| Språk: | English |
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Institute of Electrical and Electronics Engineers (IEEE)
2020
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| Länkar: | https://hdl.handle.net/1721.1/125864 |