# Questions tagged [nonlinear-optimization]

Nonlinear objectives, nonlinear constraints, non-convex objective, non-convex feasible region.

443 questions
Filter by
Sorted by
Tagged with
22 views

### Clarification of second order condition on orthogonal optimization

In the paper A Feasible Method for Optimization with Orthogonality Constraints, the arthors write: where I am confused about the notation $\mathcal{D}(\mathcal{D}\mathcal{F}(X))[Z]$. My ...
8 views

23 views

50 views

### Convergence of Quasi-Newton method with fixed derivative

Consider the Newton iteration $x^{(k+1)} = x^{(k)} - DF( x^{(k)} )^{-1} \cdot F( x^{(k)} )$ to find a zero of a function $F : \mathbb R^k \rightarrow \mathbb R^k$. If we freeze the first derivative,...
113 views

53 views

Let $(E,\mathcal E,\lambda),(E',\mathcal E',\lambda')$ be measure spaces, $I$ be a finite nonempty set, $p,q_i$ be probability densities on $(E,\mathcal E,\lambda)$, $\mu:=p\lambda$, $\varphi_i:E'\to ... 0answers 84 views ### Numerical solution of a nonlinear saddle point problem in a Hilbert space Let$(E,\mathcal E,\lambda),(E',\mathcal E',\lambda')$be measure spaces,$I$be a finite nonempty set,$p,q_i$be positive probability densities on$(E,\mathcal E,\lambda)$for$i\in I$,$\mu:=p\...
I'm trying to solve a saddle point problem of the following form: Let $(E,\mathcal E,\lambda)$ be a measure space; $p$ be a probability density on $(E,\mathcal E,\lambda)$ and $\mu:=p\lambda$ $W$ be ...