Results 271 to 280 of about 376,437 (294)

Data-Driven Choice of Smoothing Parameters

1997
This chapter is devoted to the problem of choosing the smoothing parameter of a nonparametric regression estimator, a problem that plays a major role in the remainder of this book. We will use S to denote a generic smoothing parameter when we are not referring to a particular type of smoother.
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Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1998
Jeffrey S Simonoff, Chih-Ling Tsai
exaly  

Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models

Journal of the American Statistical Association, 2004
Simon N Wood
exaly  

Application of Reinforcement Learning Algorithms for the Adaptive Computation of the Smoothing Parameter for Probabilistic Neural Network

IEEE Transactions on Neural Networks and Learning Systems, 2015
Maciej Kusy, Roman Zajdel
exaly  

Optimal Filtering and a Smoothing Algorithm for a Singular System With a Complex Stochastic Uncertain Parameter Matrix

IEEE Transactions on Circuits and Systems II: Express Briefs, 2020
Xingkai Yu, Jianxun Li
exaly  

Close-form solution and parameter selection for convex minimization-based edge-preserving smoothing

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998
Stan Z Li
exaly  

Choosing the smoothing parameter

1990
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Kalman smoothing with persistent nuisance parameters

2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2014
A. Aravkin, K. Ramamurthy, PILLONETTO, GIANLUIGI   +2 more
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Real-time local smoothing for five-axis linear toolpath considering smoothing error constraints

International Journal of Machine Tools and Manufacture, 2018
Li-Min Zhu, Jie Huang
exaly  

Stimulus smoothness influences pRF parameters

Linhardt, David, Bogner, Johanna, Woletz, Michael, Schwarzkopf, Samuel, Windischberger, Christian   +4 more
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