3. X. Wang, B. Tan, Y. Guo, T. Yang, D. Huang, L. Xu, N. Freris, H. Zhou, and X. Li, “CONFLUX: A Request-level Fusion Framework for Impression Allocation via Cascade Distillation.” Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 4070–4078, Aug. 2022.
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Pre One:2. Y. Mu and N. Freris, “Energy-aware online task dispatching and scheduling for edge systems with energy harvesting.” Accepted at the 13th IEEE International Conference on Network of the Future (NoF), Oct. 2022.
Next One:4. Y. Gong, Y. Li, and N. Freris, “FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity.” Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE), pp. 2575-2587, May 2022.
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