List questions from subgradient

Published on 22 May 2020 - 5:29

163

Views

How do you calculate the gradient of nll_loss(log_softmax(AAXW0W1)) w.r.t A?

Published on 20 Jun 2020 - 22:59

41

Views

Subgradient of a quadratic plus 1-norm

Published on 21 Jun 2020 - 1:40

258

Views

Subgradient of argmax and chain rule

Published on 07 Jul 2020 - 19:13

117

Views

Calculate a solution for matrix function

Published on 17 Jul 2020 - 11:17

211

Views

About Subdifferential of matrix norm

Published on 08 Mar 2026 - 15:46

561

Views

Integer Programming - Lagrange Multipliers - Multiple Lagrange Multipliers per Constraint

Published on 19 Jul 2020 - 2:39

649

Views

Directional derivative for function involving summation of absolute value

Published on 31 Jul 2016 - 8:22

44

Views

Non-trivial symmetric positive semidefinite matrix $M$ such that $(x_1 -x_2)^T(g_1-g_2) \ge \|x_1-x_2\|_M^2$ where $g_1,g_2$ are subgradients

Published on 17 Aug 2016 - 15:32

2k

Views

Computing subgradient of mean absolute error for linear regression

Published on 11 Oct 2016 - 10:56

5.1k

Views

Definition of subgradient of $1$-norm

Published on 25 Mar 2026 - 1:17

76

Views

Projections onto subgradients of convex functions

Published on 20 Oct 2016 - 14:25

4.1k

Views

Subdifferential of a convex differentiable function

Published on 28 Oct 2016 - 13:41

1.2k

Views

Sub-gradient and super-gradient are bounded implies globally Lipschitz.

Published on 24 Nov 2016 - 19:06

3.3k

Views

The Sub Differential of a Matrix $ {L}_{1} $ Norm

Published on 05 Dec 2016 - 15:19

List Question

Is a convex function with these properties possible?

How do you calculate the gradient of nll_loss(log_softmax(AAXW0W1)) w.r.t A?

Subgradient of a quadratic plus 1-norm

Subgradient of argmax and chain rule

Calculate a solution for matrix function

About Subdifferential of matrix norm

Integer Programming - Lagrange Multipliers - Multiple Lagrange Multipliers per Constraint

Directional derivative for function involving summation of absolute value

Non-trivial symmetric positive semidefinite matrix $M$ such that $(x_1 -x_2)^T(g_1-g_2) \ge \|x_1-x_2\|_M^2$ where $g_1,g_2$ are subgradients

Computing subgradient of mean absolute error for linear regression

Definition of subgradient of $1$-norm

Projections onto subgradients of convex functions

Subdifferential of a convex differentiable function

Sub-gradient and super-gradient are bounded implies globally Lipschitz.

The Sub Differential of a Matrix $ {L}_{1} $ Norm

Trending Questions

Popular # Hahtags

Popular Questions