Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers | Paper Citation Record

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This paper cites Sharper Convergence Guarantees for Asynchronous.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Sharper Convergence Guarantees for Asynchronous

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This paper cites Proceedings of the 39th International Conference on Machine Learning , pages =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 39th International Conference on Machine Learning , pages =

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This paper cites Asynchronous Stochastic Optimization Robust to Arbitrary Delays , url =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Asynchronous Stochastic Optimization Robust to Arbitrary Delays , url =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 34th International Conference on Machine Learning , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Revisiting Distributed Synchronous

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers International Conference on Learning Representations , year =

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This paper cites Improved Analysis of Clipping Algorithms for Non-convex Optimization , url =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Improved Analysis of Clipping Algorithms for Non-convex Optimization , url =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 40th International Conference on Machine Learning , pages =

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This paper cites Proceedings of the 38th International Conference on Machine Learning , pages =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 38th International Conference on Machine Learning , pages =

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This paper cites Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach , url =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach , url =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers 2017 , editor =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Provably Personalized and Robust Federated Learning

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers 2022 IEEE International Smart Cities Conference (ISC2) , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Electronics , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in Neural Information Processing Systems , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Adaptive Personalized Federated Learning

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Unresolved cited work

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Federated Wasserstein Distance

Reference 19

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Unresolved cited work

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Asynchronous

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Stat , volume =

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This paper cites Localized Upper and Lower Bounds for Some Estimation Problems.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Localized Upper and Lower Bounds for Some Estimation Problems

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Better Theory for

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers IEEE Transactions on Automatic Control , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in neural information processing systems , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in Neural Information Processing Systems , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers The heavy-tail phenomenon in

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 39th International Conference on Machine Learning , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Journal of Machine Learning Research , year =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers 2018 , editor =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16) , year =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 19th International Conference on Artificial Intelligence and Statistics , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in Neural Information Processing Systems , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Bertsekas and John N

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in neural information processing systems , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers IEEE transactions on automatic control , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers International conference on artificial intelligence and statistics , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Federated learning and analytics in practice: algorithms, systems, applications, and opportunities , year =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Forty-second International Conference on Machine Learning , year =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Journal of Machine Learning Research , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers ACM Computing Surveys (CSUR) , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of Machine Learning and Systems , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers OPT2020: 12th Annual Workshop on Optimization for Machine Learning , year =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers 2022 58th Annual Allerton Conference on Communication, Control, and Computing (Allerton) , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 41st International Conference on Machine Learning , series =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Understanding Priors in

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Information and Inference: A Journal of the IMA , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Presentation at Google, Mountain View, 2nd April , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Mathematical Programming , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Book in preparation for MIT Press , author =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 30th International Conference on Machine Learning , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers IEEE transactions on neural networks , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the 2016 ACM SIGSAC conference on computer and communications security , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in Neural Information Processing Systems , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers International colloquium on automata, languages, and programming , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Journal of the ACM (JACM) , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in Neural Information Processing Systems , volume =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers International Conference on Machine Learning , pages =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Science Meets Engineering of Deep Learning (SEDL) Workshop at the 33rd Conference on Neural Information Processing Systems (NeurIPS) , year =

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers From Gradient Clipping to Normalization for Heavy Tailed

Reference 63

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Observation 979f3265-5e59-4643-95e4-f05789ee6167 · outbound

This paper cites High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails , url =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails , url =

Reference 64

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Observation b9470d19-bf89-4abd-b22f-f0369a248dbc · outbound

This paper cites Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise , volume =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise , volume =

Reference 65

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Observation b7428497-890d-4e39-b010-0c1ba525c4f1 · outbound

This paper cites 2014 IEEE 55th annual symposium on foundations of computer science , pages =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers 2014 IEEE 55th annual symposium on foundations of computer science , pages =

Reference 66

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Observation 8b1ca6fa-8d83-4bef-902d-1cc88699fec1 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Foundations and trends

Reference 67

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Observation 10343d37-e780-4bdb-82e7-eaaf2d154aff · outbound

This paper cites Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data , booktitle =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data , booktitle =

Reference 68

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation d902751a-cfe7-4e28-8f36-c583868d01ec · outbound

This paper cites Brendan McMahan and Daniel Ramage and Kunal Talwar and Li Zhang , title =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Brendan McMahan and Daniel Ramage and Kunal Talwar and Li Zhang , title =

Reference 69

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation b1230fb9-1b70-458e-b191-354da5745e17 · outbound

This paper cites , title =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers , title =

Reference 70

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Observation 967718a9-d330-4ef9-b10a-5a7da8bfef01 · outbound

This paper cites Stich and Sai Praneeth Karimireddy , title =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Stich and Sai Praneeth Karimireddy , title =

Reference 71

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Observation 5946eb7d-cd5d-4861-a0a5-3d35e8ee6b8b · outbound

This paper cites Advances in neural information processing systems , volume =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in neural information processing systems , volume =

Reference 72

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation 75b7b3c5-7bc7-40a1-9010-56112499af9d · outbound

This paper cites Understanding gradient clipping in private.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Understanding gradient clipping in private

Reference 73

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation 3fe1a3bc-c9f6-42d0-8b6d-cbd434838bc0 · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Advances in Neural Information Processing Systems , volume =

Reference 74

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation 341eeb1e-6aca-430f-9b7f-c7444b8d0e4a · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Unresolved cited work

Reference 75

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Observation a681e371-19e8-49dc-957b-0d4fc97c18d8 · outbound

This paper cites 2015 , howpublished =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers 2015 , howpublished =

Reference 76

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation be5b1e73-8be8-4f28-a143-753f5cd292ad · outbound

This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Proceedings of the IEEE conference on computer vision and pattern recognition , pages =

Reference 77

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Observation 9f5d04f1-8128-4bd2-babe-800086e87b53 · outbound

This paper cites Neural computation , volume =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Neural computation , volume =

Reference 78

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation 7be2f931-904e-4247-9c5f-69ce5d90557f · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers 2024 , howpublished =

Reference 80

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation 3d60a5a7-4314-4fbe-985a-7ac92eca1a69 · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers International Conference on Learning Representations (ICLR) , year =

Reference 81

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation 652ba47a-49b0-4275-afc8-0c1240ff86e3 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Ringmaster

Reference 82

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Observation 24020692-5fe7-4604-a9d7-b26b0b6e3313 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Ringleader

Reference 83

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Observation 95981274-b4e9-432b-941d-6b706fa21297 · outbound

This paper cites Workshop on Federated Learning for Data Privacy and Confidentiality , year =.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Workshop on Federated Learning for Data Privacy and Confidentiality , year =

Reference 86

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Observation 57d70f3b-0765-4d67-b672-2ef25d210965 · outbound

This paper cites B., Mironov, I., Talwar, K., and Zhang, L.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers B., Mironov, I., Talwar, K., and Zhang, L

Reference 87

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Observation 45a51b76-6355-4314-a456-bb23d060eb36 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers and Duchi, J

Reference 88

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Observation d63093cd-129f-45c6-83c0-757395d01e44 · outbound

This paper cites I., Iusem, A.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers I., Iusem, A

Reference 89

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Observation 31ce2466-a1ee-45bf-8a48-2fbb021c8577 · outbound

This paper cites Private empirical risk minimization: Efficient algorithms and tight error bounds.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Private empirical risk minimization: Efficient algorithms and tight error bounds

Reference 90

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Observation 1e51ac29-720c-445f-ae50-0a71f3d5fd7c · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers and Hoefler, T

Reference 91

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Observation 3d0a79bf-5207-49b7-b776-c00b81aec400 · outbound

This paper cites an unresolved cited work.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Unresolved cited work

Reference 92

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation e8051056-80f7-45b7-a931-8d0882a709cf · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Revisiting Distributed Synchronous SGD

Reference 93

Resolution: verified exact; local_arxiv, observed 2026-07-03T13:58:21.754374Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1b472d28-ad50-4d27-ad1f-e9f42b5f2968 · outbound

This paper cites Z., and Hong, M.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Z., and Hong, M

Reference 94

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Observation 85e5ff03-0bf5-4854-837b-fe6dfdddabcd · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Asynchronous stochastic optimization robust to arbitrary delays

Reference 95

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Observation a106402f-62dd-488c-a012-42934248fe36 · outbound

This paper cites and Mehta, H.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers and Mehta, H

Reference 96

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Observation e75413bb-9fed-4c42-a1a3-39bb33dd85e3 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Large scale distributed deep networks

Reference 97

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Observation 2bbba582-83eb-47a1-9eaa-ae2ce3f3b0c6 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-07-03T13:58:21.771461Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation eb54e44b-f4b2-4273-a0c1-a7b8c0fa9702 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers The algorithmic foundations of differential privacy

Reference 99

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Observation aaf1c7ee-c09b-4c0b-a5f2-b5e94e28c3d2 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Unresolved cited work

Reference 100

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation ef44570b-a6eb-4f7c-a8c4-20484c1bfef5 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers R., Aytekin, A., and Johansson, M

Reference 101

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Observation c070f8db-6d0f-401d-a491-68d3cbb2442e · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers The heavy-tail phenomenon in SGD

Reference 102

Resolution: unresolved; no resolver link, observed 2026-06-27T07:23:36.879751Z

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Observation 7a1f6c6c-bc48-4be8-ab07-d65b8cf542b2 · outbound

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Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers and Yin, W

Reference 103

Resolution: verified exact; doi, observed 2026-06-27T07:30:41.379804Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 49e016e2-4ecf-4bd3-ab03-9ce763100390 · outbound

This paper cites FedML: A Research Library and Benchmark for Federated Machine Learning.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers FedML: A Research Library and Benchmark for Federated Machine Learning

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-07-03T13:58:21.760421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e96a5150-fd13-4289-a8fb-05f750b8e2f3 · outbound

This paper cites Deep residual learning for image recognition.

Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers Deep residual learning for image recognition

Reference 105

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