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AAAI
2011
14 years 7 months ago
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Byron Boots, Geoffrey J. Gordon
CVPR
2008
IEEE
16 years 9 months ago
A recursive filter for linear systems on Riemannian manifolds
We present an online, recursive filtering technique to model linear dynamical systems that operate on the state space of symmetric positive definite matrices (tensors) that lie on...
Ambrish Tyagi, James W. Davis
ICML
2004
IEEE
16 years 8 months ago
Learning low dimensional predictive representations
Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...
SPIN
2005
Springer
16 years 19 days ago
Improving Spin's Partial-Order Reduction for Breadth-First Search
We describe an improvement of the partial-order reduction algorithm for breadth-first search which was introduced in Spin version 4.0. Our improvement is based on the algorithm by...
Dragan Bosnacki, Gerard J. Holzmann
FOCS
2004
IEEE
15 years 11 months ago
Optimal Power-Down Strategies
We consider the problem of selecting threshold times to transition a device to low-power sleep states during an idle period. The two-state case in which there is a single active a...
John Augustine, Sandy Irani, Chaitanya Swamy