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» Computational Experience with the Batch Means Method
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EOR
2006
104views more  EOR 2006»
14 years 9 months ago
A wavelet-based spectral procedure for steady-state simulation analysis
We develop WASSP, a wavelet-based spectral method for steady-state simulation analysis. First WASSP determines a batch size and a warm-up period beyond which the computed batch me...
Emily K. Lada, James R. Wilson
ICIP
2007
IEEE
15 years 3 months ago
Automated Solder Inspection Method by Means of X-ray Oblique Computed Tomography
High-density LSI packages such as ball grid array (BGA) are being utilised in the car electronics and communications infrastructure products. These products require a high-speed a...
Atsushi Teramoto, Takayuki Murakoshi, Masatoshi Ts...
WSC
2007
14 years 12 months ago
Indifference-zone subset selection procedures: using sample means to improve efficiency
Two-stage selection procedures have been widely studied and applied in determining the required sample size (i.e., the number of replications or batches) for selecting the best of...
E. Jack Chen
ATAL
2007
Springer
15 years 3 months ago
Batch reinforcement learning in a complex domain
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Shivaram Kalyanakrishnan, Peter Stone
TSP
2008
89views more  TSP 2008»
14 years 9 months ago
The Kernel Least-Mean-Square Algorithm
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
Weifeng Liu, Puskal P. Pokharel, Jose C. Principe