Question

Gradient descent - does partial derivatives method always shows "real" optimum step down?

score 117 · Answer 1 · 2018-06-17 13:44:47

117

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Gradient descent - does partial derivatives method always shows "real" optimum step down?

Published on 17 Jun 2018 - 13:44

score 5.5k · Answer 2 · 2018-06-19 20:23:41

5.5k

Views

Norm of gradient in gradient descent

Published on 19 Jun 2018 - 20:23

score 34 · Answer 3 · 2018-06-22 10:50:47

34

Views

Optimization problem involving Gradient Descent where learning rate is also varying in gradient descent manner

Published on 22 Jun 2018 - 10:50

score 27 · Answer 4 · 2018-06-22 19:31:16

27

Views

In the gradient descent algorithm why do we use $r_k$ and $p_k$ for the same thing, namely the direction of the greatest descent?

Published on 22 Jun 2018 - 19:31

score 411 · Answer 5 · 2026-03-25 01:21:18

411

Views

Neural Network Gradient Descent of Cost Function Misunderstanding

Published on 25 Mar 2026 - 1:21

score 109 · Answer 6 · 2026-02-23 05:23:41

109

Views

Optimality guarantees of SGD convergence in Geometric Programming

Published on 23 Feb 2026 - 5:23

score 1.1k · Answer 7 · 2018-06-30 14:18:56

1.1k

Views

Partial Derivative of the Slope in Straight Line

Published on 30 Jun 2018 - 14:18

score 27 · Answer 8 · 2018-07-01 12:04:31

27

Views

Formalizing a Parameter Selection Problem in Machine Learning

Published on 01 Jul 2018 - 12:04

score 2.4k · Answer 9 · 2018-07-03 17:44:07

2.4k

Views

Backtracking line search algorithm - Why have non-zero alpha?

Published on 03 Jul 2018 - 17:44

score 832 · Answer 10 · 2026-03-25 07:55:23

832

Views

Minimization of positive quadratic function using gradient descent in at most $ n $ steps

Published on 25 Mar 2026 - 7:55

score 310 · Answer 11 · 2018-07-06 21:54:19

310

Views

Adapting gradient descent for numerical functional optimization?

Published on 06 Jul 2018 - 21:54

score 886 · Answer 12 · 2018-07-09 17:41:57

886

Views

Gradient Descent: Minimising the Directional Derivative in Direction $\mathbf{u}$

Published on 09 Jul 2018 - 17:41

score 416 · Answer 13 · 2026-03-22 18:18:20

416

Views

Solving for policy gradient in reinforcement learning

Published on 22 Mar 2026 - 18:18

score 367 · Answer 14 · 2018-07-10 04:50:17

367

Views

Gradient/Steepest Descent: Solving for a Step Size That Makes the Directional Derivative Vanish?

Published on 10 Jul 2018 - 4:50

score 113 · Answer 15 · 2026-03-24 21:10:43

113

Views

Finding the gradient of a variant of a total variation regularized least squares cost function

Published on 24 Mar 2026 - 21:10

List Question

Gradient descent - does partial derivatives method always shows "real" optimum step down?

Norm of gradient in gradient descent

Optimization problem involving Gradient Descent where learning rate is also varying in gradient descent manner

In the gradient descent algorithm why do we use $r_k$ and $p_k$ for the same thing, namely the direction of the greatest descent?

Neural Network Gradient Descent of Cost Function Misunderstanding

Optimality guarantees of SGD convergence in Geometric Programming

Partial Derivative of the Slope in Straight Line

Formalizing a Parameter Selection Problem in Machine Learning

Backtracking line search algorithm - Why have non-zero alpha?

Minimization of positive quadratic function using gradient descent in at most $ n $ steps

Adapting gradient descent for numerical functional optimization?

Gradient Descent: Minimising the Directional Derivative in Direction $\mathbf{u}$

Solving for policy gradient in reinforcement learning

Gradient/Steepest Descent: Solving for a Step Size That Makes the Directional Derivative Vanish?

Finding the gradient of a variant of a total variation regularized least squares cost function

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