Fetching the paper…
Reading the bibliography…
Decentralized Online Learning (online learning in decentralized networks) attracts more and more attention, since it is believed that Decentralized Online Learning can help the data providers cooperatively better solve their online problems without sharing their private data to a third party or other providers.
Tracking the best expert
M. Herbster and M. K. Warmuth · 1998
Earlier work this paper cites.
Online convex programming and generalized infinitesimal gradient ascent
M. Zinkevich · 2003
Earlier work this paper cites.
Tracking the Best of Many Experts
A. György, T. Linder, and G. Lugosi · 2005
Earlier work this paper cites.
The sinkhorn–knopp algorithm: Convergence and applications
P. Knight · 2008
Earlier work this paper cites.
Distributed Subgradient Methods for Multi-Agent Optimization
A. Nedic and A. E. Ozdaglar · 2009
Earlier work this paper cites.
Tracking recurring contexts using ensemble classifiers: An application to email filtering
I. Katakis, G. Tsoumakas, and I. Vlahavas · 2010
Earlier work this paper cites.
Introduction to online optimization, December 2011
S. Bubeck · 2011
Earlier work this paper cites.
Mirror Descent Meets Fixed Share (and feels no regret)
N. Cesa-Bianchi, P. Gaillard, G. Lugosi, and G. Stoltz · 2012
Earlier work this paper cites.
Efficient tracking of large classes of experts
A. Gyorgy, T. Linder, and G. Lugosi · 2012
Earlier work this paper cites.
Online Learning and Online Convex Optimization
S. Shalev-Shwartz · 2012
Earlier work this paper cites.
Dynamical Models and tracking regret in online convex programming
E. C. Hall and R. Willett · 2013
Earlier work this paper cites.
Online distributed optimization via dual averaging
S. Hosseini, A. Chapman, and M. Mesbahi · 2013
Earlier work this paper cites.
Distributed autonomous online learning: Regrets and intrinsic privacy-preserving properties
F. Yan, S. Sundaram, S. V. N. Vishwanathan, and Y. Qi · 2013
Earlier work this paper cites.
Communication-efficient distributed online prediction by dynamic model synchronization
M. Kamp, M. Boley, D. Keren, A. Schuster, and I. Sharfman · 2014
Earlier work this paper cites.
Online Convex Optimization in Dynamic Environments
E. C. Hall and R. M. Willett · 2015
Cited alongside, same era.
Online Optimization : Competing with Dynamic Comparators
A. Jadbabaie, A. Rakhlin, S. Shahrampour, and K. Sridharan · 2015
Cited alongside, same era.
Decentralized online optimization with global objectives and local communication
A. Nedić, S. Lee, and M. Raginsky · 2015
Cited alongside, same era.
Online learning over a decentralized network through admm
H.-F. Xu, Q. Ling, and A. Ribeiro · 2015
Cited alongside, same era.
A closer look at adaptive regret
D. Adamskiy, W. M. Koolen, A. Chernov, and V. Vovk · 2016
Cited alongside, same era.
Notes on Birkhoff-von Neumann decomposition of doubly stochastic matrices
F. Dufossé and B. U c · 2016
Cited alongside, same era.
Distributed online convex optimization on time-varying directed graphs
M. Akbari, B. Gharesifard, and T. Linder · 2017
Later among the works it cites.
Improved strongly adaptive online learning using coin betting
K.-S. Jun, F. Orabona, S. Wright, and R. Willett · 2017
Later among the works it cites.
Efficient tracking of a growing number of experts
J. Mourtada and O.-A. Maillard · 2017
Later among the works it cites.
Tracking moving agents via inexact online gradient descent algorithm
A. S. Bedi, P. Sarma, and K. Rajawat · 2018
Later among the works it cites.
Online Machine Learning in Big Data Streams
A. A. Benczúr, L. Kocsis, and R. Pálovics · 2018
Later among the works it cites.
Decentralized online learning with kernels
A. Koppel, S. Paternain, C. Richard, and A. Ribeiro · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Shifting regret, mirror descent, and matrices
A. György and C. Szepesvári · 2016
Cited alongside, same era.
Introduction to online convex optimization
E. Hazan · 2016
Cited alongside, same era.
Distributed continuous-time online optimization using saddle-point methods
S. Lee, A. Ribeiro, and M. M. Zavlanos · 2016
Cited alongside, same era.
Online optimization in dynamic environments: Improved regret rates for strongly convex problems
A. Mokhtari, S. Shahrampour, A. Jadbabaie, and A. Ribeiro · 2016
Cited alongside, same era.
Tracking the best expert in non-stationary stochastic environments
C.-Y. Wei, Y.-T. Hong, and C.-J. Lu · 2016
Cited alongside, same era.
Tracking Slowly Moving Clairvoyant - Optimal Dynamic Regret of Online Learning with True and Noisy Gradient
T. Yang, L. Zhang, R. Jin, and J. Yi · 2016
Cited alongside, same era.
Coordinate dual averaging for decentralized online optimization with nonseparable global objectives
S. Lee, A. Nedić, and M. Raginsky · 2018
Later among the works it cites.
Competing with automata-based expert sequences
M. Mohri and S. Yang · 2018
Later among the works it cites.
Distributed online optimization in dynamic environments using mirror descent
S. Shahrampour and A. Jadbabaie · 2018
Later among the works it cites.
Communication Compression for Decentralized Training
H. Tang, S. Gan, C. Zhang, T. Zhang, and J. Liu · 2018
Later among the works it cites.
Decentralized consensus optimization with asynchrony and delays
T. Wu, K. Yuan, Q. Ling, W. Yin, and A. H. Sayed · 2018
Later among the works it cites.
On nonconvex decentralized gradient descent
J. Zeng and W. Yin · 2018
Later among the works it cites.
Proximal Online Gradient is Optimum for Dynamic Regret
Y. Zhao, S. Qiu, and J. Liu · 2018
Later among the works it cites.