- DELIVER US THE MOON DATA RECOVERY UPDATE
- DELIVER US THE MOON DATA RECOVERY SOFTWARE
Zeqi Lai, Hewu Li, Yikun Wang, Qian Wu, Yangtao Deng, Jun Liu, Yuanjie Li and Jianping Wu (Tsinghua University, China) Achieving Resilient and Performance-Guaranteed Routing in Space-Terrestrial Integrated Networks.Lin Zhang (Hong Kong University of Science and Technology, Hong Kong) Shaohuai Shi (The Hong Kong University of Science and Technology, Hong Kong) Bo Li (Hong Kong University of Science and Technology, Hong Kong) Accelerating Distributed K-FAC with Efficient Collective Communication and Scheduling.
DELIVER US THE MOON DATA RECOVERY SOFTWARE
Tingting Yuan (Georg-August-University of Göttingen, Germany) Liang Mi (Nanjing University, China) Weijun Wang (Nanjing University & University of Goettingen, China) Haipeng Dai (Nanjing University & State Key Laboratory for Novel Software Technology, China) Xiaoming Fu (University of Goettingen, Germany)
AccDecoder: Accelerated Decoding for Neural-enhanced Video Analytics. A^2-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV SystemsĪndrea Coletta (JP Morgan AI Research, Italy) Flavio Giorgi, Gaia Maselli, Matteo Prata and Domenicomichele Silvestri (Sapienza University of Rome, Italy) Jonathan Ashdown (United States Air Force, USA) Francesco Restuccia (Northeastern University, USA). Ruiting Zhou (Southeast University, China) Jieling Yu and Ruobei Wang (Wuhan University, China) Bo Li (Hong Kong University of Science and Technology, Hong Kong) Jiacheng Jiang and Libing Wu (Wuhan University, China) A Reinforcement Learning Approach for Minimizing Job Completion Time in Clustered Federated Learning. Panigrahy (Yale University, USA) Don Towsley (University of Massachusetts at Amherst, USA) Shahrooz Pouryousef (University of Massachusetts Amherst MA, USA) Nitish K. A Quantum Overlay Network for Efficient Entanglement Distribution. A New Framework: Short-Term and Long-Term Returns in Stochastic Multi-Armed BanditĪbdalaziz Sawwan and Jie Wu (Temple University, USA). Xinzhe Fu (Massachusetts Institute of Technology, USA) Eytan Modiano (MIT, USA) A Learning Approach to Minimum Delay Routing in Stochastic Queueing Networks. Yongheng Deng and Ju Ren (Tsinghua University, China) Cheng Tang and Feng Lyu (Central South University, China) Yang Liu and Yaoxue Zhang (Tsinghua University, China) A Hierarchical Knowledge Transfer Framework for Heterogeneous Federated Learning. A Framework for Wireless Technology Classification using Crowdsensing PlatformsĪlessio Scalingi (IMDEA Networks, Spain) Domenico Giustiniano (IMDEA Networks Institute, Spain) Roberto Calvo-Palomino (Universidad Rey Juan Carlos, Spain) Nikolaos Apostolakis (IMDEA Networks, Spain) Gérôme Bovet (Armasuisse, Switzerland). Kengo Nakamura (NTT Corporation & Kyoto University, Japan) Takeru Inoue (NTT Network Innovation Labs., Japan) Masaaki Nishino and Norihito Yasuda (NTT Comunication Science Laboratories, Japan) Shin-ichi Minato (Kyoto University, Japan) A Fast and Exact Evaluation Algorithm for the Expected Number of Connected Nodes: an Enhanced Network Reliability Measure. Louis, USA) Wenjing Lou and Thomas Hou (Virginia Tech, USA) Yang Xiao (University of Kentucky, USA) Ning Zhang (Washington University in St. A Decentralized Truth Discovery Approach to the Blockchain Oracle Problem. A Comprehensive and Long-term Evaluation of Tor V3 Onion ServicesĬhunmian Wang, Luo Junzhou and Zhen Ling (Southeast University, China) Lan Luo (University of Central Florida, USA) Xinwen Fu (University of Massachusetts Lowell, USA). Yanbing Liu and Chunyi Peng (Purdue University, USA) 
A Close Look at 5G in the Wild: Unrealized Potentials and Implications.Yang Du, He Huang and Yu-e Sun (Soochow University, China) Kejian Li (Soochow University, Hong Kong) Boyu Zhang and Guoju Gao (Soochow University, China)
DELIVER US THE MOON DATA RECOVERY UPDATE
A Better Cardinality Estimator with Fewer Bits, Constant Update Time, and Mergeability.Zai Shi (The Ohio State University, USA) Yilin Zheng (the Ohio State University, USA) Atilla Eryilmaz (The Ohio State University, USA) A Bayesian Framework for Online Nonconvex Optimization over Distributed Processing Networks.List of Accepted Papers in IEEE INFOCOM 2023 Main Conference
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