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Absorbtion spectrometry
Affine function
Affine set
Angle between vectors
Auto-regressive models for time-series prediction
Backward substition method for solving triangular systems of linear equations
Bag-of-word representation of text
Basis of a subspace
Beer-Lambert law
CAT scan imaging
Cauchy-Schwartz inequality
Cardinality of a vector
Cardinality minimization, see also -norm
Circuit design via Geometric Programming
Combinational logic in circuit design
Componentwise inequality between vectors
Condition number of a matrix
Convex function
Convex optimization problem
Covariance matrix
CVX
Determinant of a square matrix
Dimension of an affine set
Domain of a function
Duality: weak, strong
Dual norm
Dual problem
Dual function
Dual norm, see also norm
Dyad
Eigenvalue decomposition (EVD) of a square, symmetric matrix
Epigraph of a function
Expected value of a random variable
Feasible point, feasible set
First-order approximation
Frobenius norm of a matrix
Function
Fundamental theorem of linear algebra
Geometric program (GP)
Global optimum
Gradient of a function
Gradient methods, for solving convex programs
Gram matrix
Gram-Schmidt (GS) procedure
Graph of a function
Half-space
Hessian of a function
Hyperplane
Image compression
Incidence matrix of a graph
Independent set of vectors
Interior-point methods, for solving convex programs
Inverse of a matrix
Jacobian matrix of a non-linear map
Kernel matrix, kernel trick
Laplacian of a graph
Lagragian of an optimization problem
Laplace formula for the determinant of a matrix
Largest singular value (LSV) norm of a matrix
Least-squares
Leibnitz formula for the determinant of a matrix
Left inverse of a matrix
Linear function
Linear matrix inequality
Linear program (LP)
Linear regression
Local optimum
Log-return of a financial asset
Log-sum-exp function
norms of a vector: norm, -norm (also called Euclidean norm), norm.
norm, or cardinality, of a vector.
Maps
Matrix
Matrix-vector product
Sample Mean
Minimax inequality
Norms: general definition, for vectors, for matrices; see also dual norm
Nullspace of a matrix
Optimal point, optimal value, optimal set
Orthogonal: vectors, matrices
Permutation matrix
Point-wise maximum of functions
Polyhedron
Polyhedral function
Positive-definite
Power laws
Principal Component Analysis (PCA)
Probability simplex
Projection: on a line
Pseudo-inverse of a matrix
Quadratic program (QP)
Quadratic form, quadratic function
Range of a matrix
Rank of a matrix
Rate of return of a financial asset
Rayleigh quotient
Regression: Linear
Right inverse of a matrix
Robust linear program
Sample mean, sample standard deviation, sample covariance matrix
Scalar product: for vectors, for matrices
Second-order approximation of a function
Second-order cone
Second-order cone program (SOCP)
Semidefinite program (SDP)
Singular value of a general matrix
Singular value decomposition (SVD)
Slater's condition for strong duality
Spectral theorem, or symmetric eigenvalue decomposition (SED) theorem
Symmetric matrix
Tomography
Trace of a matrix
Triangle inequality
Triangular matrices
Triangular systems of linear equations, see also backward substitution algorithm
Unconstrained optimization
Unitary matrix (see also Orthogonal matrix)
Vectors
Sample Variance