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In many areas, practitioners need to analyze large datasets that challenge conventional single-machine computing.
Distribution of eigenvalues for some sets of random matrices
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Variance estimation in high-dimensional linear models
L. H. Dicker · 2014
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Optimality guarantees for distributed statistical estimation
J. C. Duchi, M. I. Jordan, M. J. Wainwright, and Y. Zhang · 2014
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D. Paul and A. Aue · 2014
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Large Sample Covariance Matrices and High-Dimensional Data Analysis
J. Yao, Z. Bai, and S. Zheng · 2015
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Divide and conquer kernel ridge regression: A distributed algorithm with minimax optimal rates
Y. Zhang, J. Duchi, and M. Wainwright · 2015
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Divide and conquer in non-standard problems and the super-efficiency phenomenon
M. Banerjee, C. Durot, and B. Sen · 2016
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S.-B. Lin, X. Guo, and D.-X. Zhou · 2017
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Computational limits of a distributed algorithm for smoothing spline
Z. Shang and G. Cheng · 2017
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Distributed inference for quantile regression processes
S. Volgushev, S.-K. Chao, and G. Cheng · 2017
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Distributed testing and estimation under sparse high dimensional models
H. Battey, J. Fan, H. Liu, J. Lu, and Z. Zhu · 2018
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Distributed linear regression by averaging
E. Dobriban and Y. Sheng · 2018
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High-dimensional asymptotics of prediction: Ridge regression and classification
E. Dobriban and S. Wager · 2018
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Distributed nearest neighbor classification
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Aggregated inference
X. Huo and S. Cao · 2018
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Algorithmic aspects of parallel data processing
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How many machines can we use in parallel computing for kernel ridge regression?
M. Liu, Z. Shang, and G. Cheng · 2018
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Caring without sharing: Meta-analysis 2.0 for massive genome-wide association studies
A. Pourshafeie, C. D. Bustamante, and S. Prabhu · 2018
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A massive data framework for m-estimators with cubic-rate
C. Shi, W. Lu, and R. Song · 2018
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Distributed inference for linear support vector machine
X. Wang, Z. Yang, X. Chen, and W. Liu · 2018
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Distributed nonparametric regression under communication constraints
Y. Zhu and J. Lafferty · 2018
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T. T. Cai and H. Wei · 2020
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