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Differential privacy is concerned about the prediction quality while measuring the privacy impact on individuals whose information is contained in the data.
An algorithm for quadratic programming
M. Frank and P. Wolfe · 1956
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Submodular Functions and Convexity
L. Lovász · 1982
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The Nature of Statistical Learning Theory
V. N. Vapnik · 1995
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Convex Analysis
R. T. Rockafellar · 1997
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Submodular Functions and Optimization
S. Fujishige · 2005
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Calibrating noise to sensitivity in private data analysis
C. Dwork, F. McSherry, K. Nissim, and A. Smith · 2006
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A note on differential privacy: Defining resistance to arbitrary side information
S. P. Kasiviswanathan and A. D. Smith · 2008
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On the duality of strong convexity and strong smoothness : Learning applications and matrix regularization
S. Kakade and Shalev-Shwartz · 2009
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Stochastic convex optimization
S. Shalev-Shwartz, O. Shamir, N. Srebro, and K. Sridharan · 2009
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Structured Sparsity-inducing Norms Through Submodular Functions
F. Bach · 2010
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Differentially Private Empirical Risk Minimization
K. Chaudhuri, C. Monteleoni, and A. D. Sarwate · 2011
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Private Convex Empirical Risk Minimization and High-dimensional Regression
D. Kifer, A. Smith, and A. Thakurta · 2012
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Convex relaxation for combinatorial penalties
G. Obozinski and F. Bach · 2012
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Learning with Submodular Functions: A Convex Optimization Perspective
F. Bach · 2013
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The Algorithmic Foundations of Differential Privacy
C. Dwork and A. Roth · 2014
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(Near) Dimension Independent Risk Bounds for Differentially Private Learning
P. Jain and A. Thakurta · 2014
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Private Empirical Risk Minimization Beyond the Worst Case: The Effect of the Constraint Set Geometry
K. Talwar, A. Thakurta, and L. Zhang · 2014
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Nearly-optimal Private LASSO
K. Talwar, A. Thakurta, and L. Zhang · 2015
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Deep Learning with Differential Privacy
M. Abadi, A. Chu, I. Goodfellow, H. B. McMahan, I. Mironov, K. Talwar, and L. Zhang · 2016
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Differentially Private Empirical Risk Minimization Revisited: Faster and More General
D. Wang, M. Ye, and J. Xu · 2017
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Revisiting Frank-Wolfe: Projection-free sparse convex optimization
M. Jaggi · 2013
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Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds
R. Bassily, A. Smith, and A. Thakurta · 2014
Cited alongside, same era.
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Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics
X. Wu, F. Li, A. Kumar, K. Chaudhuri, S. Jha, and J. Naughton · 2017
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Efficient private ERM for smooth objectives
J. Zhang, K. Zheng, W. Mou, and L. Wang · 2017
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