4 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.DC2021★ 2 cited
Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning
Shijian Li, Oren Mangoubi, Lijie Xu +1
Stochastic Gradient Descent (SGD) has become the de facto way to train deep neural networks in distributed clusters. A critical factor in determining the training throughput and mo…
cs.PF2019★ 4 cited
Speeding up Deep Learning with Transient Servers
Shijian Li, Robert J. Walls, Lijie Xu +1
Distributed training frameworks, like TensorFlow, have been proposed as a means to reduce the training time of deep learning models by using a cluster of GPU servers. While such sp…
cs.GT2019★ 2 cited
Incentivizing the Workers for Truth Discovery in Crowdsourcing with Copiers
Lingyun Jiang, Xiaofu Niu, Jia Xu +2
Crowdsourcing has become an efficient paradigm for performing large scale tasks. Truth discovery and incentive mechanism are fundamentally important for the crowdsourcing system. M…