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Ensuring privacy of sensitive data is essential in many contexts, such as healthcare data, banks, e-commerce, wireless sensor networks, and social networks.
“Protocols for secure computations,”
A. C. Yao, · 1982
Earlier work this paper cites.
Parallel and Distributed Computation: Numerical Methods
D.P. Bertsekas and J.N. Tsitsiklis, · 1997
Earlier work this paper cites.
The Foundations of Cryptography
O. Goldreich, · 2004
Earlier work this paper cites.
Convex Optimization
S. Boyd and L. Vandenberghe, · 2004
Earlier work this paper cites.
“Theory and practice of multiparty computation,”
I. Damgård, · 2006
Earlier work this paper cites.
Theory of Cryptography
C. Dwork, F. McSherry, K. Nissim, and A. Smith, · 2006
Earlier work this paper cites.
“Privacy-preserving classification of horizontally partitioned data via random kernels,”
O. L. Mangasarian and E. W. Wild, · 2008
Earlier work this paper cites.
“Privacy-preserving classification of vertically partitioned data via random kernels,”
O. L. Mangasarian, E. W. Wild, and G. M. Fung, · 2008
Earlier work this paper cites.
“Solving linear programs using multiparty computation,”
T. Toft, · 2009
Cited alongside, same era.
“Hiccups on the road to privacy-preserving linear programming,”
A. Bednarz, N. Bean, and M. Roughan, · 2009
Cited alongside, same era.
“Differentially private approximation algorithms,”
A. Gupta, K. Ligett, F. McSherry, A. Roth, and K. Talwar, · 2010
Cited alongside, same era.
“Differentially private empirical risk minimization,”
K. Chaudhuri, C. Monteleoni, and A. D. Sarwate, · 2011
Cited alongside, same era.
“Privacy-preserving linear programming,”
O. L. Mangasarian, · 2011
Cited alongside, same era.
“Privacy-preserving linear and nonlinear approximation via linear programming,”
O. L. Mangasarian, · 2011
Cited alongside, same era.
Methods for Two-Party Privacy-Preserving Linear Programming
A. Bednarz, · 2012
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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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“Differentially private filtering,”
J. L. Ny and G. J. Pappas, · 2012
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“Differentially private kalman filtering,”
J. L. Ny and G. J. Pappas, · 2012
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“Privacy-preserving horizontally partitioned linear programs,”
O. L. Mangasarian, · 2012
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A Course in Real Analysis
J. N. McDonald and N. A. Weiss, · 2013
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“Differentially private distributed optimization, submitted,”
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“Practical privacy-preserving multiparty linear programming based on problem transformation,”
J. Dreier and F. Kerschbaum, · 2011
Cited alongside, same era.
“Secure and practical outsourcing of linear programming in cloud computing,”
C. Wang, K. Ren, and J. Wang, · 2011
Cited alongside, same era.
Z. Huang, S. Mitra, and N. Vaidya, · 2014
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