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ICML
2005
IEEE
16 years 7 months ago
Reinforcement learning with Gaussian processes
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
Yaakov Engel, Shie Mannor, Ron Meir
WSC
2004
15 years 7 months ago
An Experimental Study on Forecasting Using TES Processes
Forecasting is of prime importance for accuracy in decision making. For data sets containing high autocorrelations, failure to account for temporal dependence will result in poor ...
Abdullah S. Karaman, Tayfur Altiok
ENGL
2007
103views more  ENGL 2007»
15 years 6 months ago
Fault Diagnosis of Manufacturing Processes via Genetic Algorithm Approach
—Instantaneous detection and diagnosis of various faults and break-downs in industrial processes is required to reduce production losses and damage to equipments. A solved knowle...
Stefania Gallova
AIPS
2008
15 years 8 months ago
Stochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
Jia-Hong Wu, Rajesh Kalyanam, Robert Givan

Book
361views
17 years 3 months ago
Introduction to Statistical Signal Processing
"A random or stochastic process is a mathematical model for a phenomenon that evolves in time in an unpredictable manner from the viewpoint of the observer. The phenomenon m...
R.M. Gray