Fetching the paper…
Reading the bibliography…
Continual data collection and widespread deployment of machine learning algorithms, particularly the distributed variants, have raised new privacy challenges.
H. Whitney, “Congruent graphs and the connectivity of graphs,”
1932
Earlier work this paper cites.
D. P. Bertsekas, “On the Goldstein-Levitin-Polyak gradient projection method,”
1976
Earlier work this paper cites.
A. Shamir, “How to share a secret,”
1979
Earlier work this paper cites.
L. Lamport, R. Shostak, and M. Pease, “The byzantine generals problem,”
1982
Earlier work this paper cites.
S. Goldwasser, “Multi party computations: past and present,” in
1997
Earlier work this paper cites.
H. S. Hippert, C. E. Pedreira, and R. C. Souza, “Neural networks for short-term load forecasting: A review and evaluation,”
2001
Earlier work this paper cites.
B. Pinkas, “Cryptographic techniques for privacy-preserving data mining,”
2002
Earlier work this paper cites.
Athena Scientific, 2003
D. P. Bertsekas, A. Nedić, A. E. Ozdaglar, · 2003
Earlier work this paper cites.
M. Rabbat and R. Nowak, “Distributed optimization in sensor networks,” in
2004
Earlier work this paper cites.
J. Cortes, S. Martinez, and F. Bullo, “Spatially-distributed coverage optimization and control with limited-range interactions,”
2005
Earlier work this paper cites.
W. Ren, R. W. Beard, and E. M. Atkins, “A survey of consensus problems in multi-agent coordination,” in
2005
Earlier work this paper cites.
R. Diestel, “Graph theory. 2005,”
2005
Earlier work this paper cites.
A. Nedić and A. Ozdaglar, “On the rate of convergence of distributed subgradient methods for multi-agent optimization,”
2007
Earlier work this paper cites.
R. Olfati-Saber, “Distributed tracking for mobile sensor networks with information-driven mobility,” in
2007
Earlier work this paper cites.
D. Zelazo, A. Rahmani, and M. Mesbahi, “Agreement via the edge laplacian,” in
2007
Earlier work this paper cites.
S. S. Ram, A. Nedić, and V. V. Veeravalli, “Incremental stochastic subgradient algorithms for convex optimization,”
2009
Earlier work this paper cites.
J. Vaidya, “Privacy-preserving linear programming,” in
2009
Earlier work this paper cites.
Cambridge university press, 2009
O. Goldreich, · 2009
Earlier work this paper cites.
S. S. Ram, A. Nedić, and V. V. Veeravalli, “Distributed stochastic subgradient projection algorithms for convex optimization,”
2010
Earlier work this paper cites.
T. W. Judson, “Abstract algebra,” 2010
2010
Earlier work this paper cites.
Springer, 2010
R. B. Bapat, · 2010
Earlier work this paper cites.
S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, “Distributed optimization and statistical learning via the alternating direction method of multipliers,”
2011
Earlier work this paper cites.
A. Agarwal and J. C. Duchi, “Distributed delayed stochastic optimization,” in
2011
Cited alongside, same era.
A. Nedić, “Asynchronous broadcast-based convex optimization over a network,”
2011
Cited alongside, same era.
C. Wang, K. Ren, and J. Wang, “Secure and practical outsourcing of linear programming in cloud computing,” in
2011
Cited alongside, same era.
J. Dreier and F. Kerschbaum, “Practical privacy-preserving multiparty linear programming based on problem transformation,” in
2011
Cited alongside, same era.
Y. Nesterov, “Efficiency of coordinate descent methods on huge-scale optimization problems,”
2012
Cited alongside, same era.
M. Zhu and S. Martínez, “On distributed convex optimization under inequality and equality constraints,”
A. Nedić and A. Olshevsky, “Distributed Optimization Over Time-Varying Directed Graphs,”
2015
Later among the works it cites.
J. Liu and S. J. Wright, “Asynchronous stochastic coordinate descent: Parallelism and convergence properties,”
2015
Later among the works it cites.
A. Nedić and A. Olshevsky, “Distributed Optimization Over Time-Varying Directed Graphs,”
2015
Later among the works it cites.
Z. Huang, S. Mitra, and N. Vaidya, “Differentially private distributed optimization,” in
2015
Later among the works it cites.
R. Shokri and V. Shmatikov, “Privacy-Preserving Deep Learning,”
2015
Later among the works it cites.
R. Shokri and V. Shmatikov, “Privacy-preserving deep learning,” in
2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2012
Cited alongside, same era.
MIT Press, 2012
S. Sra, S. Nowozin, and S. J. Wright, · 2012
Cited alongside, same era.
E. A. Abbe, A. E. Khandani, and A. W. Lo, “Privacy-preserving methods for sharing financial risk exposures,”
2012
Cited alongside, same era.
M. Alizadeh, T.-H. Chang, and A. Scaglione, “Grid integration of distributed renewables through coordinated demand response,” in
2012
Cited alongside, same era.
F. Pasqualetti, F. Dörfler, and F. Bullo, “Cyber-physical security via geometric control: Distributed monitoring and malicious attacks,” in
2012
Cited alongside, same era.
2012
Cited alongside, same era.
PhD thesis, 2012
A. Bednarz, · 2012
Cited alongside, same era.
S. Gade, A. A. Paranjape, and S.-J. Chung, “Herding a flock of birds approaching an airport using an unmanned aerial vehicle,” in
2015
Later among the works it cites.
2015
Later among the works it cites.
2015
Later among the works it cites.
C. Li and P. Zhou, “Differentially private distributed online learning,”
2015
Later among the works it cites.
2016
Closest in time.
2016
Closest in time.
2016
Closest in time.
C. N. Hadjicostis, N. H. Vaidya, and A. D. Domínguez-García, “Robust distributed average consensus via exchange of running sums,”
2016
Closest in time.
L. Su and N. H. Vaidya, “Fault-tolerant multi-agent optimization: Optimal iterative distributed algorithms,” in
2016
Closest in time.
Accessed: 2016-10-16
“SwiftKey.” · 2016
Closest in time.
H. B. McMahan, E. Moore, D. Ramage,
2016
Closest in time.
Y. Hong, J. Vaidya, N. Rizzo, and Q. Liu, “Privacy preserving linear programming,”
2016
Closest in time.
S. Han, U. Topcu, and G. J. Pappas, “Differentially private distributed constrained optimization,”
2016
Closest in time.
S. Gade and N. Vaidya, “Distributed optimization of convex sum of non-convex functions,”
2016
Closest in time.
Cengage Learning, 2016
J. Gallian, · 2016
Closest in time.