On quadratic and OnL convergence of a predictor-corrector algorithm for LCP

On Superlinear Convergence of Infeasible Interior-PointAlgorithms for Linearly Constrained Convex Programs

Computational Optimization and Applications

On the Rate of Local Convergence of High-Order-Infeasible-Path-Following Algorithms for P*-Linear Complementarity Problems

Computational Optimization and Applications

A Global Linear and Local Quadratic Continuation Smoothing Method for Variational Inequalities with Box Constraints

Computational Optimization and Applications

A Smoothing Newton-Type Algorithm of Stronger Convergence for the Quadratically Constrained Convex Quadratic Programming

Computational Optimization and Applications

Enlarging neighborhoods of interior-point algorithms for linear programming via least values of proximity measure functions

Applied Numerical Mathematics

Mehrotra-type predictor-corrector algorithm revisited

Optimization Methods & Software - Dedicated to Professor Michael J.D. Powell on the occasion of his 70th birthday

A polynomial path-following interior point algorithm for general linear complementarity problems

Journal of Global Optimization

On a Class of Superlinearly Convergent Polynomial Time Interior Point Methods for Sufficient LCP

SIAM Journal on Optimization

Corrector-predictor methods for sufficient linear complementarity problems

Computational Optimization and Applications

Superlinear Convergence of an Infeasible Predictor-Corrector Path-Following Interior Point Algorithm for a Semidefinite Linear Complementarity Problem Using the Helmberg-Kojima-Monteiro Direction

SIAM Journal on Optimization

Mehrotra-type predictor-corrector algorithms for sufficient linear complementarity problem

Applied Numerical Mathematics

A new O(nL) -iteration predictor-corrector algorithm with wide neighborhood for semidefinite programming

Journal of Computational and Applied Mathematics

Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory

The Journal of Machine Learning Research