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TSP
2011
230views more  TSP 2011»
11 years 4 months ago
Bayesian Nonparametric Inference of Switching Dynamic Linear Models
—Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
NIPS
2008
11 years 11 months ago
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
Many nonlinear dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
HYBRID
2000
Springer
12 years 1 months ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
NIPS
2000
11 years 11 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
ICMLA
2008
11 years 11 months ago
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
Silvia Chiappa
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