Ridgelets: Estimating with Ridge Functions
نویسنده
چکیده
Feedforward neural networks, projection pursuit regression, and more generally, estimation via ridge functions have been proposed as an approach to bypass the curse of dimensionality and are now becoming widely applied to approximation or prediction in applied sciences. To address problems inherent to these methods – ranging from the construction of neural networks to their efficiency and capability – Candes (1999d) developed a new system that allows the representation of arbitrary functions as superpositions of specific ridge functions, the ridgelets.
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تاریخ انتشار 2007