58 citations · 67 across the 10 of their papers we have counts for
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cs.LG2023
Killing Two Birds with One Stone: Quantization Achieves Privacy in Distributed Learning
Guangfeng Yan, Tan Li, Kui Wu +1
Communication efficiency and privacy protection are two critical issues in distributed machine learning. Existing methods tackle these two issues separately and may have a high imp…
cs.LG2021
On the Difficulty of Generalizing Reinforcement Learning Framework for Combinatorial Optimization
Mostafa Pashazadeh, Kui Wu
Combinatorial optimization problems (COPs) on the graph with real-life applications are canonical challenges in Computer Science. The difficulty of finding quality labels for probl…
cs.LG2021★ 6 cited
FedNILM: Applying Federated Learning to NILM Applications at the Edge
Yu Zhang, Guoming Tang, Qianyi Huang +3
Non-intrusive load monitoring (NILM) helps disaggregate the household's main electricity consumption to energy usages of individual appliances, thus greatly cutting down the cost i…