Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác. An accelerated communication-efficient primal-dual optimization framework for structured machine learning. Optimization Methods and Software, 36(1):20-44, 2021. [doi]
@article{MaJCST21,
title = {An accelerated communication-efficient primal-dual optimization framework for structured machine learning},
author = {Chenxin Ma and Martin Jaggi and Frank E. Curtis and Nathan Srebro and Martin Takác},
year = {2021},
doi = {10.1080/10556788.2019.1650361},
url = {https://doi.org/10.1080/10556788.2019.1650361},
researchr = {https://researchr.org/publication/MaJCST21},
cites = {0},
citedby = {0},
journal = {Optimization Methods and Software},
volume = {36},
number = {1},
pages = {20-44},
}