The DOI matches its OpenAlex record; 21 of the 21 references it cites were found in a registry or an index.
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server
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Cites
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Pregel: a system for large-scale graph processing
Malewicz, G., Austern, M. H., Bik, A. J. C., Dehnert, J. C., Horn, I., Leiser, N., & Czajkowski, G. (2010) · Proceedings of the 2010 ACM SIGMOD International Conference on Management of data · doi:10.1145/1807167.1807184 · Cited by 3,515
Large Scale Distributed Deep Networks
Dean, J. B., Corrado, G. S., Monga, R., Chen, K., Devin, M., Mao, M., Ranzato, M., Senior, A., Tucker, P. A., Yang, K., et al. (2012) · Cited by 3,199
Time, clocks, and the ordering of events in a distributed system
Massachusetts Computer Associates, I., & Lamport, L. (2019) · Concurrency: the Works of Leslie Lamport · doi:10.1145/3335772.3335934 · Cited by 1,979
Distributed GraphLab: a framework for machine learning and data mining in the cloud
Low, Y., Bickson, D., Gonzalez, J., Guestrin, C., Kyrola, A., & Hellerstein, J. M. (2012) · Proceedings of the VLDB Endowment · doi:10.14778/2212351.2212354 · Cited by 1,653
Virtual Time and Global States of Distributed Systems
Mattern, F. (2002) · Cited by 1,277
Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
Niu, F., Recht, B., Re, C., & Wright, S. J. (2011) · arXiv · doi:10.48550/arxiv.1106.5730 · Cited by 1,211
Parallelized Stochastic Gradient Descent
Zinkevich, M., Weimer, M., Li, L., & Smola, A. J. (2010) · Cited by 1,124
Large-scale matrix factorization with distributed stochastic gradient descent
Gemulla, R., Nijkamp, E., Haas, P. J., & Sismanis, Y. (2011) · Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/2020408.2020426 · Cited by 589
Design and evaluation of a conit-based continuous consistency model for replicated services
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Cited by
Federated Machine Learning: Concept and Applications
Yang, Q., Liu, Y., Chen, T., & Tong, Y. (2019) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3298981 · Cited by 6,322
A survey on federated learning
Zhang, C., Xie, Y., Bai, H., Yu, B., Li, W., & Gao, Y. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.106775 · Cited by 1,899
A review of applications in federated learning
Li, L., Fan, Y., Tse, M., & Lin, K.-Y. (2020) · Computers & Industrial Engineering · doi:10.1016/j.cie.2020.106854 · Cited by 1,559
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Li, Q., Wen, Z., Wu, Z., Hu, S., Wang, N., Li, Y., Liu, X., & He, B. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2021.3124599 · Cited by 1,407
Scaling Distributed Machine Learning with the Parameter Server
Li, M. (2014) · Proceedings of the 2014 International Conference on Big Data Science and Computing · doi:10.1145/2640087.2644155 · Cited by 979
Metadata
- Authors
- Ho, Q., Cipar, J., Cui, H., Kim, J. K., Lee, S., Gibbons, P. B., Gibson, G. A., Ganger, G. R., & Xing, E. P.
- Venue
- PubMed
- Publisher
- National Institutes of Health
- Published
- 2013-01-01
- Volume
- 2013
- Pages
- 1223-1231
- OpenAlex
- W2132737349
- Cited by
- 506
- References
- 21
- FWCI
- 32.02
- Type
- journal article
- Language
- en
- Open access
- green
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- The paper
- Ho, Q., Cipar, J., Cui, H., Kim, J. K., Lee, S., Gibbons, P. B., Gibson, G. A., Ganger, G. R., & Xing, E. P. (2013). More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server. PubMed. https://doi.org/10.1184/r1/6475898
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
