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An Introduction to Stochastic Deep Learning. [PDF]
Wiley Interdiscip Rev Comput StatLiang F.
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Adaptive Visual Sensing Deviation Detection and Real-Time Tracking Control of Swing-Arc Narrow-Gap Weld Based on Variation Coefficient Recognition. [PDF]
Sensors (Basel)Wang J, Su N, Wang J.
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Robust Augmented-Diffusion Filtered-x Maximum Correntropy Criterion for Distributed Active Noise Control Under Impulsive Noise. [PDF]
Entropy (Basel)Peng D, He Y, Liu Q.
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An intelligent weighted adaptive regression process for reliable and uncertainty aware drought forecasting. [PDF]
iScienceJia H +3 more
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An Intelligent Disassembly Sequence Optimisation Framework for End-of-Life EV Batteries Using Adaptive Operator Selection. [PDF]
Biomimetics (Basel)Huang J +6 more
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Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05), 2005
Mining frequent patterns is a fundamental part of data mining. Most of the previous studies adopt an a priori-like candidate set generation-and-test approach. The a priori is the first algorithm which uses the a priori property to prune the search space.
Cornelia Györödi +4 more
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Mining frequent patterns is a fundamental part of data mining. Most of the previous studies adopt an a priori-like candidate set generation-and-test approach. The a priori is the first algorithm which uses the a priori property to prune the search space.
Cornelia Györödi +4 more
openaire +2 more sources
Architecture adaptive algorithms
Parallel Computing, 1993zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Arnold R. Krommer +1 more
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