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Learning to Quantize Deep Neural Networks: A Competitive-Collaborative Approach.

, , , and . DAC, page 1-6. IEEE, (2020)

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Take It or Leave It: A Survey Study on Operating System Upgrade Practices., , , , and . ACSAC, page 490-504. ACM, (2018)FedRule: Federated Rule Recommendation System with Graph Neural Networks., , , , , and . IoTDI, page 197-208. ACM, (2023)Adaptive Distillation: Aggregating Knowledge from Multiple Paths for Efficient Distillation., , , and . BMVC, page 100. BMVA Press, (2021)Distributionally Robust Federated Averaging., , and . NeurIPS, (2020)Distributed Personalized Empirical Risk Minimization., , , and . CoRR, (2023)CAPTAIN: Comprehensive Composition Assistance for Photo Taking., , and . ACM Trans. Multim. Comput. Commun. Appl., 18 (1): 14:1-14:24 (2022)Targeted Data-driven Regularization for Out-of-Distribution Generalization., , , and . KDD, page 882-891. ACM, (2020)FedRule: Federated Rule Recommendation System with Graph Neural Networks., , , , , and . CoRR, (2022)Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking., , , , , , , and . NeurIPS, (2023)Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 2545-2554. PMLR, (2019)