NeurIPS 2018oral115 citations
Spectral Filtering for General Linear Dynamical Systems
Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang
Abstract
We give a polynomial-time algorithm for learning latent-state linear dynamical systems without system identification, and without assumptions on the spectral radius of the system's transition matrix. The algorithm extends the recently introduced technique of spectral filtering, previously applied only to systems with a symmetric transition matrix, using a novel convex relaxation to allow for the efficient identification of phases.
BibTeX
@inproceedings{NEURIPS2018_d6288499,
author = {Hazan, Elad and Lee, Holden and Singh, Karan and Zhang, Cyril and Zhang, Yi},
booktitle = {Advances in Neural Information Processing Systems},
editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Spectral Filtering for General Linear Dynamical Systems},
url = {https://proceedings.neurips.cc/paper_files/paper/2018/file/d6288499d0083cc34e60a077b7c4b3e1-Paper.pdf},
volume = {31},
year = {2018}
}