Fetching the paper…
Reading the bibliography…
We propose Zeno++, a new robust asynchronous Stochastic Gradient Descent~(SGD) procedure which tolerates Byzantine failures of the workers.
Gradient methods for minimizing functionals
Polyak, B. T · 1963
Earlier work this paper cites.
The Byzantine Generals Problem
Lamport, L., Shostak, R., and Pease, M · 1982
Earlier work this paper cites.
Robust Statistics , volume 523
Huber, P. J · 2004
Earlier work this paper cites.
Learning Multiple Layers of Features from Tiny Images
Krizhevsky, A · 2009
Earlier work this paper cites.
Slow Learners are Fast
Zinkevich, M., Langford, J., and Smola, A. J · 2009
Earlier work this paper cites.
Feng, J., Xu, H., and Mannor, S · 2014
Earlier work this paper cites.
Fault-Tolerant Multi-Agent Optimization: Optimal Iterative Distributed Algorithms
Su, L. and Vaidya, N. H · 2016
Earlier work this paper cites.
Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent
Blanchard, P., Mhamdi, E. M. E., Guerraoui, R., and Stainer, J · 2017
Earlier work this paper cites.
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
Chen, Y., Su, L., and Xu, J · 2017
Cited alongside, same era.
Pointer Sentinel Mixture Models
Merity, S., Xiong, C., Bradbury, J., and Socher, R · 2017
Cited alongside, same era.
Asynchronous Stochastic Gradient Descent with Delay Compensation
Zheng, S., Meng, Q., Wang, T., Chen, W., Yu, N., Ma, Z., and Liu, T.-Y · 2017
Cited alongside, same era.
Byzantine Stochastic Gradient Descent
Alistarh, D., Allen-Zhu, Z., and Li, J · 2018
Cited alongside, same era.
Robust Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers
Cao, X. and Lai, L · 2018
Cited alongside, same era.
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Chen, L., Wang, H., Charles, Z. B., and Papailiopoulos, D. S · 2018
Cited alongside, same era.
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
Dutta, S., Joshi, G., Ghosh, S., Dube, P., and Nagpurkar, P · 2018
Later among the works it cites.
Asynchronous Decentralized Parallel Stochastic Gradient Descent
Lian, X., Zhang, W., Zhang, C., and Liu, J · 2018
Later among the works it cites.
The Hidden Vulnerability of Distributed Learning in Byzantium
Mhamdi, E. M. E., Guerraoui, R., and Rouault, S · 2018
Later among the works it cites.
Defending non-Bayesian learning against adversarial attacks
Su, L. and Vaidya, N. H · 2018
Later among the works it cites.
Phocas: Dimensional Byzantine-resilient Stochastic Gradient Descent
Xie, C., Koyejo, O., and Gupta, I · 2018
Later among the works it cites.
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Asynchronous Byzantine Machine Learning (the case of SGD)
Damaskinos, G., Mhamdi, E. M. E., Guerraoui, R., Patra, R., and Taziki, M · 2018
Cited alongside, same era.
SLSGD: Secure and Efficient Distributed On-device Machine Learning
Xie, C., Koyejo, O., and Gupta, I
Cited in the paper.
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance
Xie, C., Koyejo, S., and Gupta, I
Cited in the paper.
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
Xie, C., Koyejo, S., and Gupta, I
Cited in the paper.
Yin, D., Chen, Y., Ramchandran, K., and Bartlett, P · 2018
Later among the works it cites.
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
Zhou, Z., Mertikopoulos, P., Bambos, N., Glynn, P. W., Ye, Y., Li, L.-J., and Fei-Fei, L · 2018
Later among the works it cites.