Question

Which are the alternative approaches to stochastic (online) gradient descend for online optimization?

score 27 · Answer 1 · 2026-03-29 02:36:21

27

Views

Which are the alternative approaches to stochastic (online) gradient descend for online optimization?

Published on 29 Mar 2026 - 2:36

score 48 · Answer 2 · 2016-04-11 13:19:20

48

Views

Minimize/Maximze a function against its approximation.

Published on 11 Apr 2016 - 13:19

score 1.2k · Answer 3 · 2016-04-17 19:53:58

1.2k

Views

How does one rigorously prove that gradient descent indeed decreases the function in question locally i.e. show $f(x^{(t+1)}) \leq f(x^{(t)})$?

Published on 17 Apr 2016 - 19:53

score 2.5k · Answer 4 · 2016-04-18 02:56:48

2.5k

Views

Correct formulation of equality and non-negativity constrained non-linear minimization problem

Published on 18 Apr 2016 - 2:56

score 67 · Answer 5 · 2016-04-25 22:09:27

67

Views

Numerical stability of computational results

Published on 25 Apr 2016 - 22:09

score 68 · Answer 6 · 2016-05-21 07:03:43

68

Views

Calculating block diagonalization / canonical bases with linear optimization?

Published on 21 May 2016 - 7:03

score 757 · Answer 7 · 2016-05-27 11:49:09

757

Views

Computational complexity of conjugate gradient method for a positive semidefinite Hermitian matrix

Published on 27 May 2016 - 11:49

score 397 · Answer 8 · 2026-03-30 07:43:42

397

Views

Index of a stationary point of constrained optimization

Published on 30 Mar 2026 - 7:43

score 221 · Answer 9 · 2016-06-04 10:06:06

221

Views

Rate of Convergence vs Tolerance

Published on 04 Jun 2016 - 10:06

score 182 · Answer 10 · 2016-06-04 17:03:38

182

Views

Does convergence of iterates imply convergence of function values?

Published on 04 Jun 2016 - 17:03

score 925 · Answer 11 · 2026-03-29 07:38:42

925

Views

Can someone help me understand using the Jacobian matrix with Newton's Method for finding zeros?

Published on 29 Mar 2026 - 7:38

score 58 · Answer 12 · 2016-06-06 06:39:05

58

Views

How can I solve this optimization problem?

Published on 06 Jun 2016 - 6:39

score 1.3k · Answer 13 · 2026-03-18 14:24:31

1.3k

Views

Decrease in the size of gradient in gradient descent

Published on 18 Mar 2026 - 14:24

score 91 · Answer 14 · 2026-03-30 23:20:28

91

Views

Check numerically the definite-positiveness on linear subspaces

Published on 30 Mar 2026 - 23:20

score 33 · Answer 15 · 2016-06-12 20:17:00

33

Views

Numerical Method for fitting parameters of an explicit integration to actual data

Published on 12 Jun 2016 - 20:17

List Question

Which are the alternative approaches to stochastic (online) gradient descend for online optimization?

Minimize/Maximze a function against its approximation.

How does one rigorously prove that gradient descent indeed decreases the function in question locally i.e. show $f(x^{(t+1)}) \leq f(x^{(t)})$?

Correct formulation of equality and non-negativity constrained non-linear minimization problem

Numerical stability of computational results

Calculating block diagonalization / canonical bases with linear optimization?

Computational complexity of conjugate gradient method for a positive semidefinite Hermitian matrix

Index of a stationary point of constrained optimization

Rate of Convergence vs Tolerance

Does convergence of iterates imply convergence of function values?

Can someone help me understand using the Jacobian matrix with Newton's Method for finding zeros?

How can I solve this optimization problem?

Decrease in the size of gradient in gradient descent

Check numerically the definite-positiveness on linear subspaces

Numerical Method for fitting parameters of an explicit integration to actual data

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