78 citations · 265 across the 23 of their papers we have counts for
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math.OC2019★ 47 cited
ADMM for Efficient Deep Learning with Global Convergence
Junxiang Wang, Fuxun Yu, Xiang Chen +1
Alternating Direction Method of Multipliers (ADMM) has been used successfully in many conventional machine learning applications and is considered to be a useful alternative to Sto…
math.OC2019★ 3 cited
The Application of Multi-block ADMM on Isotonic Regression Problems
Junxiang Wang, Liang Zhao
The multi-block ADMM has received much attention from optimization researchers due to its excellent scalability. In this paper, the multi-block ADMM is applied to solve two large-s…
math.OC2019
Convergence and Applications of ADMM on the Multi-convex Problems
Junxiang Wang, Liang Zhao
In recent years, although the Alternating Direction Method of Multipliers (ADMM) has been empirically applied widely to many multi-convex applications, delivering an impressive per…