Deterministic algorithms for matrix completion
By Eyal Heiman, Gideon Schechtman, Adi Shraibman. 2014
34 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Mechanics, Algorithms & Complexity
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Yuanzhi Li
- Yingyu Liang
- Zeyuan Allen-Zhu
- Tengyu Ma
- Prateek Jain
- Quanquan Gu
- Andrej Risteski
- Srinadh Bhojanapalli
In Computational Mechanics
- Yuanzhi Li
- Srinadh Bhojanapalli
- Yingyu Liang
- Andrej Risteski
- Prateek Jain
- Troy Lee
- Adi Shraibman
- Zeyuan Allen-Zhu
In Algorithms & Complexity
Citations in the corpus
- Recovery guarantee of weighted low-rank approximation via alternating minimization (2016, background): “The only relaxations to random sampling to the best of our knowledge are in (Heiman et al., 2014; Lee & Shraibman, 2013; Bhojanapalli & Jain, 2014).”
- Matrix Completion From any Given Set of Observations (2013, background): “In this paper we continue the work started in [9], and give a simple and general answer to this second question.”
- Universal Matrix Completion (2014, methodology): “Our second results shows that if M satisfies both A 1 and A 2, then using nuclear-norm minimization based method, P Ω ( M ) can be used to recover back M exactly.”