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NIPS
2003
15 years 8 months ago
Nonstationary Covariance Functions for Gaussian Process Regression
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...
Christopher J. Paciorek, Mark J. Schervish
ARC
2007
Springer
152views Hardware» more  ARC 2007»
15 years 6 months ago
Statistical signal processing approaches to fault detection
: The parity space approach to fault detection and isolation (FDI) has been developed during the last twenty years, and the focus here is to describe its application to stochastic ...
Fredrik Gustafsson
CORR
2010
Springer
174views Education» more  CORR 2010»
15 years 6 months ago
Gaussian Process Bandits for Tree Search
We motivate and analyse a new Tree Search algorithm, based on recent advances in the use of Gaussian Processes for bandit problems. We assume that the function to maximise on the ...
Louis Dorard, John Shawe-Taylor
IJVR
2008
169views more  IJVR 2008»
15 years 6 months ago
Agent Architecture for a Real World Autonomous Virtual Guide: Interaction between the Decision and Perception Processes and Envi
Museums like marine aquariums are facing a difficult problem when trying to deliver information to their visitors. The exhibits they propose are dynamic by definition. Each may con...
Morgan Veyret, Eric Maisel, Jacques Tisseau
KES
2010
Springer
15 years 5 months ago
Evolving takagi sugeno modelling with memory for slow processes
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with lo...
Simon McDonald, Plamen P. Angelov