Paper "In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle" accepted for presentation at SIGMOD 2022

The following paper has been accepted for presentation at external pageSIGMOD 2022call_made:

"In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle" by Lijie Xu (ETH Zurich), Shuang Qiu (University of Chicago), Binhang Yuan (ETH Zurich), Jiawei Jiang (ETH Zurich), Cedric Renggli (ETH Zurich), Shaoduo Gan (ETH Zurich), Kaan Kara (ETH Zurich), Guoliang Li (Tsinghua University), Ji Liu (Kwai Inc.), Wentao Wu (Microsoft Research), Jieping Ye (Didi Chuxing & University of Michigan), Ce Zhang (ETH Zurich).