List questions from numerical-optimization

Published on 24 May 2017 - 8:33

79

Views

Fixed Point Scheme

Published on 26 Mar 2026 - 21:53

463

Views

Efficient algorithm to find a symmetric matrix that commute with a given set of matrices

Published on 26 May 2017 - 20:30

265

Views

Estimating the convexity of black box objective function , by multi starting a gradient based method.

Published on 30 May 2017 - 10:00

118

Views

How can I efficiently find a matrix D such that the cost function $||(M-D\cdot N)||$ is minimized?

Published on 31 May 2017 - 23:19

73

Views

Show that Newton's method used to find $\sqrt[m]{R}$ applied to $x^m-R$ and to $1-\frac{R}{x^m}$ converges at different rates.

Published on 29 Mar 2026 - 12:39

1.1k

Views

Constrained optimization of a cost function for a matrix

Published on 02 Jun 2017 - 13:54

141

Views

Reducing sensitivity to initial guess for this nonconvex optimization problem

Published on 02 Jun 2017 - 21:10

43

Views

Optimization with probability constrain

Published on 04 Jun 2017 - 17:19

5.3k

Views

Why do we need to check both primal and dual feasibility in LP programs?

Published on 05 Jun 2017 - 2:20

1.1k

Views

Dogleg Method versus Constrained (Quasi)Newton's Step

Published on 05 Jun 2017 - 17:54

68

Views

which numerical method for solving $f(x) = 0$ if the solution is unique?

Published on 07 Jun 2017 - 20:53

415

Views

Conjugate gradient - gradients orthogonality proof

Published on 09 Jun 2017 - 1:30

1.9k

Views

Why do we need gradient descent to minimize a cost function?

Published on 29 Mar 2026 - 14:01

69

Views

Is there any method for gradient descent that achieves acceleration while moving always in the opposite direction of the gradient?

Published on 31 Mar 2026 - 5:23

List Question

root finding for a tangent-like function

Fixed Point Scheme

Efficient algorithm to find a symmetric matrix that commute with a given set of matrices

Estimating the convexity of black box objective function , by multi starting a gradient based method.

How can I efficiently find a matrix D such that the cost function $||(M-D\cdot N)||$ is minimized?

Show that Newton's method used to find $\sqrt[m]{R}$ applied to $x^m-R$ and to $1-\frac{R}{x^m}$ converges at different rates.

Constrained optimization of a cost function for a matrix

Reducing sensitivity to initial guess for this nonconvex optimization problem

Optimization with probability constrain

Why do we need to check both primal and dual feasibility in LP programs?

Dogleg Method versus Constrained (Quasi)Newton's Step

which numerical method for solving $f(x) = 0$ if the solution is unique?

Conjugate gradient - gradients orthogonality proof

Why do we need gradient descent to minimize a cost function?

Is there any method for gradient descent that achieves acceleration while moving always in the opposite direction of the gradient?

Trending Questions

Popular # Hahtags

Popular Questions