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AAAI
2006
13 years 9 months ago
Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
David Wingate, Satinder P. Singh
JMLR
2006
105views more  JMLR 2006»
13 years 7 months ago
Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems
We introduce a method for approximate smoothed inference in a class of switching linear dynamical systems, based on a novel form of Gaussian Sum smoother. This class includes the ...
David Barber
PC
2010
145views Management» more  PC 2010»
13 years 6 months ago
GPU computing with Kaczmarz's and other iterative algorithms for linear systems
The graphics processing unit (GPU) is used to solve large linear systems derived from partial differential equations. The differential equations studied are strongly convection-...
Joseph M. Elble, Nikolaos V. Sahinidis, Panagiotis...
EUROPAR
2009
Springer
14 years 2 months ago
PSPIKE: A Parallel Hybrid Sparse Linear System Solver
The availability of large-scale computing platforms comprised of tens of thousands of multicore processors motivates the need for the next generation of highly scalable sparse line...
Murat Manguoglu, Ahmed H. Sameh, Olaf Schenk
CDC
2010
IEEE
140views Control Systems» more  CDC 2010»
13 years 2 months ago
On the observability of linear systems from random, compressive measurements
Abstract-- Recovering or estimating the initial state of a highdimensional system can require a potentially large number of measurements. In this paper, we explain how this burden ...
Michael B. Wakin, Borhan Molazem Sanandaji, Tyrone...