Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Iterative Concave Rank Approximation for Recovering Low-Rank Matrices
Fixed Point and Bregman Iterative Methods for Matrix Rank Minimization
Tensor theta norms and low rank recovery
Nonconvex Splitting for Regularized Low-Rank + Sparse Decomposition
Low-rank matrix completion by riemannian optimization
tensor completion and lown - rank tensor recovery via convex optimization .
Adaptive Sampling and Fast Low-Rank Matrix Approximation
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
GoDec+: Fast and Robust Low-Rank Matrix Decomposition Based on Maximum Correntropy
Low-rank optimization with convex constraints
Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm
Low-rank matrix completion using alternating minimization
Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition
sparse and low - rank matrix decomposition via alternating direction methods .
Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing
Sharp analysis of low-rank kernel matrix approximations
Low rank tensor recovery via iterative hard thresholding
Guaranteed Rank Minimization via Singular Value Projection
Fast smooth rank approximation for tensor completion
Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees
Iteratively re-weighted least squares minimization for sparse recovery
Reconfigurable Routers for Low Power and High Performance
Second-Order Consensus for Multiagent Systems With Directed Topologies and Nonlinear Dynamics
New classes of degree sequences with fast mixing swap Markov chain sampling
bregman iterative algorithms for \ ell1 - minimization with applications to compressed sensing .
Ultra-low voltage and low power ring oscillator for wireless sensor network using CMOS varactor