Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Kronecker Determinantal Point Processes
fixed - point algorithms for learning determinantal point processes .
A new metric on the manifold of kernel matrices with application to matrix geometric means
Learning the Kernel Matrix with Semi-Definite Programming
A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices
Lattice Point Enumeration on Block Reduced Bases
Algorithms for projecting points onto conics
Probability Product Kernels
Statistics of critical points of Gaussian fields on large-dimensional spaces.
Random Projections on Manifolds of Symmetric Positive Definite Matrices for Image Classification
Positive Definite Kernels in Machine Learning
A General Projection Property for Distribution Families
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence
On the Geometry of Covariance Matrices
Overlapping Mixtures of Gaussian Processes for the Data Association Problem
Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices
A fast algorithm for the minimum covariance determinant estimator
A Simple Proof of the Restricted Isometry Property for Random Matrices
Capacity-Constrained Delaunay Triangulation for point distributions
Cones of matrices and set-functions and 0-1 optimization
Gender and ethnicity classification using deep learning in heterogeneous face recognition
The influence of intrinsic and extrinsic motivation on individuals' knowledge sharing behavior
Manopt, a Matlab toolbox for optimization on manifolds
CompostBin: A DNA composition-based algorithm for binning environmental shotgun reads
Permuted successive cancellation decoder for polar codes