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» Using Gaussian Processes to Optimize Expensive Functions
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NIPS
2008
13 years 11 months ago
Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
John W. Roberts, Russ Tedrake
IR
2002
13 years 10 months ago
Threshold Setting and Performance Optimization in Adaptive Filtering
An experimental adaptive filtering system, built on the Okapi search engine, is described. In addition to the regular text retrieval functions, the system requires a complex set o...
Stephen E. Robertson
IJCV
2006
107views more  IJCV 2006»
13 years 10 months ago
Image Deblurring in the Presence of Impulsive Noise
Consider the problem of image deblurring in the presence of impulsive noise. Standard image deconvolution methods rely on the Gaussian noise model and do not perform well with imp...
Leah Bar, Nahum Kiryati, Nir A. Sochen
ICANN
2009
Springer
14 years 4 months ago
Adaptive Feature Transformation for Image Data from Non-stationary Processes
Abstract. This paper introduces the application of the feature transformation approach proposed by Torkkola [1] to the domain of image processing. Thereto, we extended the approach...
Erik Schaffernicht, Volker Stephan, Horst-Michael ...
FPGA
1999
ACM
174views FPGA» more  FPGA 1999»
14 years 2 months ago
Reduction of Latency and Resource Usage in Bit-Level Pipelined Data Paths for FPGAs
Pipelining of data path structures increases the throughput rate at the expense of enlarged resource usage and latency unless architectures optimized towards specific applications...
Peter Kollig, Bashir M. Al-Hashimi