Understand
Over the past decade there has been considerable interest in spectral algorithms for learning Predictive State Representations (PSRs).
- Spectral algorithms have appealing theoretical guarantees; however, the resulting models do not always perform well on inference tasks in practice.
- One reason for this behavior is the mismatch between the intended task (accurate filtering or prediction) and the loss function being optimized by the algorithm (estimation error in model parameters).
- A natural idea is to improve performance by refining PSRs using an algorithm such as EM.
Built on
On the convergence properties of the em algorithm
Wu, C. F. Jeff · 1983
Earlier work this paper cites.
Observable operator models for discrete stochastic time series
Jaeger, Herbert · 1999
Earlier work this paper cites.
Predictive representations of state
Littman, Michael L., Sutton, Richard S., and Singh, Satinder · 2001
Earlier work this paper cites.
Predictive state representations: A new theory for modeling dynamical systems
Singh, Satinder, James, Michael R., and Rudary, Matthew R · 2004
Earlier work this paper cites.
Closing the learning-planning loop with predictive state representations
Boots, Byron, Siddiqi, Sajid M., and Gordon, Geoffrey J · 2009
Earlier work this paper cites.
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Predictive state temporal difference learning
Boots, Byron and Gordon, Geoffrey J · 2010
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Learning message-passing inference machines for structured prediction
Ross, Stéphane, Munoz, Daniel, Hebert, Martial, and Bagnell, J. Andrew · 2011
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Supervised learning for dynamical system learning
Hefny, Ahmed, Downey, Carlton, and Gordon, Geoffrey J · 2015
Cited alongside, same era.
Then
Learning latent variable models by improving spectral solutions with exterior point methods
Shaban, Amirreza, Farajtabar, Mehrdad, Xie, Bo, Song, Le, and Boots, Byron · 2015
Later among the works it cites.
Improving predictive state representations via gradient descent
Jiang, Nan, Kulesza, Alex, and Singh, Satinder P · 2016
Later among the works it cites.
Learning to filter with predictive state inference machines
Sun, Wen, Venkatraman, Arun, Boots, Byron, and Bagnell, J. Andrew · 2016
Later among the works it cites.
Online instrumental variable regression with applications to online linear system identification
Venkatraman, Arun, Sun, Wen, Hebert , Martial, Bagnell, J. Andrew (Drew), and Boots, Byron · 2016
Later among the works it cites.
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