Computational Limits of A Distributed Algorithm For Smoothing Spline

zbMath1442.90055arXiv1512.09226MaRDI QIDQ4637031

Zuofeng Shang, Guang Cheng

Publication date: 17 April 2018

Full work available at URL: https://arxiv.org/abs/1512.09226

zbMATH Keywords

smoothing splinedivide-and-conquercomputational limitssplitotic theory

Mathematics Subject Classification ID

Deterministic scheduling theory in operations research (90B35) Queues and service in operations research (90B22)

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Cites Work

• Unnamed Item
• A partially linear framework for massive heterogeneous data
• Optimal estimation of the mean function based on discretely sampled functional data: phase transition
• Maximum penalized likelihood estimation. Volume II: Regression
• Time series: theory and methods
• Asymptotically minimax hypothesis testing for nonparametric alternatives. III
• Local and global asymptotic inference in smoothing spline models
• Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
• Mathematical Statistics

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