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Advanced Topics in AI for Networking (Winter 2022/2023): Difference between revisions
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Advanced Topics in AI for Networking (Winter 2022/2023) (view source)
Revision as of 13:19, 4 November 2022
, 4 November 2022→List of Papers
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==List of Papers == | ==List of Papers == | ||
1. Genet: automatic curriculum generation for learning adaptation in networking [https://dl.acm.org/doi/10.1145/3544216.3544243] | 1. Genet: automatic curriculum generation for learning adaptation in networking [https://dl.acm.org/doi/10.1145/3544216.3544243] [Celine] | ||
2. Multi-resource interleaving for deep learning training [https://dl.acm.org/doi/10.1145/3544216.3544224] | 2. Multi-resource interleaving for deep learning training [https://dl.acm.org/doi/10.1145/3544216.3544224] | ||
3. NeuroScaler: neural video enhancement at scale [https://dl.acm.org/doi/10.1145/3544216.3544218] [Tim] | 3. NeuroScaler: neural video enhancement at scale [https://dl.acm.org/doi/10.1145/3544216.3544218] [Tim] | ||
4. Deep Interest Network for Click-Through Rate Prediction [https://arxiv.org/pdf/1706.06978.pdf] | 4. Deep Interest Network for Click-Through Rate Prediction [https://arxiv.org/pdf/1706.06978.pdf] | ||
5. Reducing the Service Function Chain Backup Cost over the Edge and Cloud by a Self-Adapting Scheme [https://ieeexplore.ieee.org/document/9312434] [Tim] | 5. Reducing the Service Function Chain Backup Cost over the Edge and Cloud by a Self-Adapting Scheme [https://ieeexplore.ieee.org/document/9312434] [Tim] | ||
6. Routing on Multiple Optimality Criteria[https://dl.acm.org/doi/pdf/10.1145/3387514.3405864] | 6. Routing on Multiple Optimality Criteria[https://dl.acm.org/doi/pdf/10.1145/3387514.3405864] | ||
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7. Understanding, Detecting and Localizing Partial Failures in Large System Software [https://www.cs.jhu.edu/~huang/paper/omegagen-nsdi20-preprint.pdf] | 7. Understanding, Detecting and Localizing Partial Failures in Large System Software [https://www.cs.jhu.edu/~huang/paper/omegagen-nsdi20-preprint.pdf] | ||
8. Understanding Lifecycle Management Complexity of Datacenter Topologies [https://www.cs.jhu.edu/~huang/paper/omegagen-nsdi20-preprint.pdf] | 8. Understanding Lifecycle Management Complexity of Datacenter Topologies [https://www.cs.jhu.edu/~huang/paper/omegagen-nsdi20-preprint.pdf] [Celine] | ||
9. ACC: Automatic ECN Tuning for High-Speed Datacenter Networks [https://dl.acm.org/doi/pdf/10.1145/3452296.3472927][Tim] | 9. ACC: Automatic ECN Tuning for High-Speed Datacenter Networks [https://dl.acm.org/doi/pdf/10.1145/3452296.3472927] [Tim] | ||
10. Seven Years in the Life of Hypergiants’ Off-Nets [https://dl.acm.org/doi/pdf/10.1145/3452296.3472928] | 10. Seven Years in the Life of Hypergiants’ Off-Nets [https://dl.acm.org/doi/pdf/10.1145/3452296.3472928] [Celine] | ||
11. ATP: In-network Aggregation for Multi-tenant Learning [https://www.usenix.org/system/files/nsdi21-lao.pdf] | 11. ATP: In-network Aggregation for Multi-tenant Learning [https://www.usenix.org/system/files/nsdi21-lao.pdf] | ||