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The maximum correlation of functions of a pair of random variables is an important measure of stochastic dependence.
A class of statistics with asymptotically normal distribution
Wassily Hoeffding · 1948
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Some properties of the bivariate normal distribution considered in the form of a contingency table
Henry Oliver Lancaster · 1957
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The strong law of large numbers for u-statistics
Wassily Hoeffding · 1961
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The jackknife estimate of variance
Bradley Efron and Charles Stein · 1981
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Projection pursuit regression
Jerome H Friedman and Werner Stuetzle · 1981
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Generalized additive models
Trevor Hastie and Robert Tibshirani · 1986
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Linear smoothers and additive models
Andreas Buja, Trevor Hastie, and Robert Tibshirani · 1989
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Comparison results for the lower tail of gaussian seminorms
Wenbo V Li · 1992
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Remarks on the maximum correlation coefficient
Amir Dembo, Abram Kagan, and Lawrence A Shepp · 2001
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Basic properties of strong mixing conditions. a survey and some open questions
Richard C Bradley et al · 2005
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On the maximum correlation coefficient
Wlodzimierz Bryc, Amir Dembo, and Abram Kagan · 2005
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On the maximal correlation coefficient
Yaming Yu · 2008
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Simultaneous analysis of lasso and dantzig selector
Peter J Bickel, Ya’acov Ritov, and Alexandre B Tsybakov · 2009
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On the conditions used to prove oracle results for the lasso
Sara A van de Geer and Peter Bühlmann · 2009
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Sparsity in multiple kernel learning
Vladimir Koltchinskii and Ming Yuan · 2010
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Minimax-optimal rates for sparse additive models over kernel classes via convex programming
Garvesh Raskutti, Martin J Wainwright, and Bin Yu · 2012
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Fast learning rate of multiple kernel learning: Trade-off between sparsity and smoothness
Taiji Suzuki and Masashi Sugiyama · 2013
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Doubly penalized estimation in additive regression with high-dimensional data
Zhiqiang Tan and Cun-Hui Zhang · 2017
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Generalized additive models: an introduction with R
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Lukas Meier, Sara Van de Geer, and Peter Bühlmann · 2009
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Simon N Wood · 2017
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