Rank Minimization or Nuclear-Norm Minimization: Are We Solving the Right Problem?

@article{Dai2014RankMO,
  title={Rank Minimization or Nuclear-Norm Minimization: Are We Solving the Right Problem?},
  author={Yuchao Dai and Hongdong Li},
  journal={2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)},
  year={2014},
  pages={1-8}
}
Low rank method or rank-minimization has received considerable attention from recent computer vision community. Due to the inherent computational complexity of rank problems, the non-convex rank function is often relaxed to its convex relaxation, i.e. the nuclear norm. Thanks to recent progress made in the filed of compressive sensing (CS), vision researchers who are practicing CS are fully aware, and conscious, of the convex relaxation gap, as well as under which condition (e.g. Restricted… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-6 OF 6 CITATIONS

Weighted Nuclear Norm and TV Regularization based Image Deraining

  • 2018 Twenty Fourth National Conference on Communications (NCC)
  • 2018
VIEW 18 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Global Optimality in Inductive Matrix Completion

  • 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2018
VIEW 1 EXCERPT
CITES BACKGROUND

Compact Matrix Factorization with Dependent Subspaces

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2017
VIEW 1 EXCERPT
CITES BACKGROUND

Dynamic Behavior Analysis via Structured Rank Minimization

  • International Journal of Computer Vision
  • 2016
VIEW 3 EXCERPTS
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-10 OF 32 REFERENCES

Robust Recovery of Subspace Structures by Low-Rank Representation

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2013
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

A Newton-like method for solving rank constrained linear matrix inequalities

  • 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)
  • 2004
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

The generalized trace-norm and its application to structure-from-motion problems

  • 2011 International Conference on Computer Vision
  • 2011
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL