Most local convergence analyses of the sequential quadratic programming (SQP) algorithm for nonlinear programming make strong assumptions about the solution, namely, that the activ...
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
This paper investigates the rate of convergence of an alternative approximation method for stochastic differential equations. The rates of convergence of the one-step and multi-st...
We show that an interior-pointmethodfor monotonevariationalinequalitiesexhibits superlinear convergence provided that all the standard assumptions hold except for the well-known as...
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...
One of the key issues in decentralized beamforming is the need to phasealign the carriers of all the sensors in the network. Recent work in this area has shown the viability of ce...
Abstract. A new iterative algorithm for the solution of minimization problems in infinitedimensional Hilbert spaces which involve sparsity constraints in form of p-penalties is pro...
The computation of a rigid body transformation which optimally aligns a set of measurement points with a surface and related registration problems are studied from the viewpoint o...
Helmut Pottmann, Qi-Xing Huang, Yong-Liang Yang, S...