Simultaneous Learning of Non-Linear Manifold and Dynamical Models for High-Dimensional Time Series

Simultaneous Learning of Non-Linear Manifold and Dynamical Models for High-Dimensional Time Series

The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relation...

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Bibliographic Details
Main Author: Li, Rui
Language:en_US
Published: Boston University Computer Science Department 2011
Online Access:Li, Rui. "Simultaneous Learning Of Non-Linear Manifold And Dynamical Models For High-Dimensional Time Series (PhD Thesis)", Technical Report BUCS-TR-2009-027, Computer Science Department, Boston University, August 10, 2009. [Available from: http://hdl.handle.net/2144/1751]
https://hdl.handle.net/2144/1751

Internet

Li, Rui. "Simultaneous Learning Of Non-Linear Manifold And Dynamical Models For High-Dimensional Time Series (PhD Thesis)", Technical Report BUCS-TR-2009-027, Computer Science Department, Boston University, August 10, 2009. [Available from: http://hdl.handle.net/2144/1751]
https://hdl.handle.net/2144/1751

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