L1-regularized least squares, with the ability of discovering sparse representations, is quite prevalent in the field of machine learning, statistics and signal processing. In this paper, we propose a novel algorithm called Dual Projected Newton Method (DPNM) to solve the 1-regularized least squares problem. In DPNM, we first derive a new dual problem as a box constrained quadratic programming....

We show how the quasi-Newton least squares method (QN-LS) relates to Krylov subspace methods in general and to GMRes in particular.

This paper shows a new approach for non-linear least squares fitting with NURBS as curves and surfaces to measured data by the Gauss-Newton method. A Trust Region algorithm is used to reach global convergence as well as variable substitution and simple bounds. Key–Words: Non-linear least squares, NURBS, curve and surface fitting, reverse engineering, optimisation, GaussNewton

we present a structured algorithm for solving constrained nonlinear least squares problems, and establish its local two-step q-superlinear convergence. the approach is based on an adaptive structured scheme due to mahdavi-amiri and bartels of the exact penalty method of coleman and conn for nonlinearly constrained optimization problems. the structured adaptation also makes use of the ideas of n...

Quasi-Newton methods have played a prominent role, over many years, in the design of effective practical methods for the numerical solution of nonlinear minimization problems and in multi-dimensional zero-finding. There is a wide literature outlining the properties of these methods and illustrating their performance [e.g., [8]]. In addition, most modern optimization libraries house a quasi-Newt...

A least-squares mixed nite element formulation is applied to the nonlinear elliptic problems arising in each time-step of an implicit Euler discretization for variably saturated ow problems. This approach simultaneously constructs approximations to the ux in Raviart-Thomas spaces and to the hydraulic potential by standard H 1-conforming linear nite elements. Two important properties of the leas...

Newton-Raphson State Estimation method using bus admittance matrix remains as an efficient and most popular method to estimate the state variables. Elements of Jacobian matrix are computed from standard expressions which lack physical significance. In this paper, elements of the state estimation Jacobian matrix are obtained considering the power flow measurements in the network elements. These ...