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A Machine Learning Approach of Load Balance Routing to Support Next-Generation Wireless Networks. In IWCMC ."},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"crossref","unstructured":"Hong Zhang Junxue Zhang Wei Bai Kai Chen and Mosharaf Chowdhury. 2017. Resilient datacenter load balancing in the wild. In ACM SIGCOMM.  Hong Zhang Junxue Zhang Wei Bai Kai Chen and Mosharaf Chowdhury. 2017. Resilient datacenter load balancing in the wild. In ACM SIGCOMM .","DOI":"10.1145\/3098822.3098841"},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"crossref","unstructured":"Junxue Zhang Wei Bai and Kai Chen. 2019. Enabling ECN for datacenter networks with RTT variations. In ACM CoNEXT.  Junxue Zhang Wei Bai and Kai Chen. 2019. Enabling ECN for datacenter networks with RTT variations. In ACM CoNEXT .","DOI":"10.1145\/3359989.3365426"},{"key":"e_1_3_2_2_63_1","unstructured":"Martin Zinkevich. 2003. Online convex programming and generalized infinitesimal gradient ascent. In ICML.  Martin Zinkevich. 2003. 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