Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Robust Principal Component Analysis with Non-Greedy l1-Norm Maximization
R1-PCA: rotational invariant L1-norm principal component analysis for robust subspace factorization
A randomized algorithm for principal component analysis
A partially parallel splitting method for multiple-block separable convex programming with applications to robust PCA
Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA
EM Algorithms for PCA and SPCA
Sparse probabilistic principal component analysis
An Overview of Robust Subspace Recovery
Probabilistic Principal Component Analysis
Complexity Theoretic Lower Bounds for Sparse Principal Component Detection
Robust 1-bit Compressed Sensing and Sparse Logistic Regression: A Convex Programming Approach
Guaranteed Rank Minimization via Singular Value Projection
Nonnegative Sparse PCA
Optimal exact least squares rank minimization
Convex Sparse PCA for Unsupervised Feature Learning
Robust Linear Optimization under General Norms
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems
Sparse Algorithm for Robust LSSVM in Primal Space
Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling
Linearized augmented Lagrangian and alternating direction methods for nuclear norm minimization
Robust Principal Component Analysis on Graphs
Pictures of pain: their contribution to the neuroscience of empathy
Spectral Relaxation for K means Clustering
Samaretta perexilis, a new genus and new species of samarid flatfish (Pleuronectiformes: Samaridae) from the South Pacific
Triangle mesh-based edge detection and its application to surface segmentation and adaptive surface smoothing
A model for estimating agile project process and schedule acceleration