Terkko Navigator / Optimization methods and software

Separation theorems for the extrema of best piecewise monotonic approximations to successive data

Trust-region algorithms for training responses: machine learning methods using indefinite Hessian approximations

The‘Idiot’ crash quadratic penalty algorithm for linear programming and its application to linearizations of quadratic assignment problems

An Alternating Augmented Lagrangian method for constrained nonconvex optimization

Preface

Analysis of the gradient method with an Armijo–Wolfe line search on a class of non-smooth convex functions

A concise second-order complexity analysis for unconstrained optimization using high-order regularized models

ADMM for multiaffine constrained optimization

Error estimates for iterative algorithms for minimizing regularized quadratic subproblems

Stochastic polynomial optimization

Computation of second-order directional stationary points for group sparse optimization

Preface

On black-box optimization in divide-and-conquer SAT solving

ADMM for multiaffine constrained optimization

Computation of second-order directional stationary points for group sparse optimization

A concise second-order complexity analysis for unconstrained optimization using high-order regularized models

Integer linear programming formulations for double roman domination problem

Symmetric rank-1 approximation of symmetric high-order tensors

Analysis of the gradient method with an Armijo–Wolfe line search on a class of non-smooth convex functions

Error estimates for iterative algorithms for minimizing regularized quadratic subproblems

New versions of Newton method: step-size choice, convergence domain and under-determined equations

A derivative-free -algorithm for convex finite-max problems

Relaxation schemes for mathematical programmes with switching constraints

A robust multi-batch L-BFGS method for machine learning

A generic coordinate descent solver for non-smooth convex optimisation

Stochastic polynomial optimization

Accelerated multiple step-size methods for solving unconstrained optimization problems

Adjoint-based SQP method with block-wise quasi-Newton Jacobian updates for nonlinear optimal control

Adaptive online distributed optimization in dynamic environments

Improving the performance of DICOPT in convex MINLP problems using a feasibility pump

A convergent Newton algorithm for computing Z-eigenvalues of an almost nonnegative irreducible tensor

A generic framework for approximation analysis of greedy algorithms for star bicoloring

An accelerated communication-efficient primal-dual optimization framework for structured machine learning

An interior point method designed for solving linear quadratic optimal control problems with hp finite elements