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Nonparametric Regression Estimation with Incomplete Data: Minimax Global Convergence Rates and Adaptivity
Adaptivity Besov spaces inhomogeneous data minimax estimation
2011/7/6
We consider the nonparametric regression estimation problem of recovering an unknown response function $f$ on the basis of incomplete data when the design points follow a known density $g$ with a fini...
Consolidation theories and push-down accounting: achieving global convergence
consolidation theory push-down accounting global convergence
2010/10/18
This paper examines the parent, entity, and traditional theories of consolidation
with a focus on the relevance and representational faithfulness of the information each
provides to decision makers....
Global convergence of quorum-sensing networks
quorum-sensing networks synchronization phenomena
2010/4/6
In many natural synchronization phenomena, communication between individual elements occurs not directly, but rather through the environment. One of these instances is bacterial quorum sensing, where ...
Global Convergence of a Modified SQP Method for Mathematical Programs With Inequalities and Equalities Constraints
Nonlinear Programs Inequalities and Equalities System Sequential quadratic programming
2008/7/1
When we solve an ordinary nonlinear programming problem by the most and popular sequential quadratic programming (SQP) method, one of the difficulties that we must overcome is to ensure the consistenc...
Global Convergence of the Broyden's Class of Quasi-Newton Methods with Nonmonotone Linesearch
quasi-newton method broyden class
2007/12/11
In this paper, the Broyden class of quasi-Newton methods for unconstrained optimization is investigated. Non-monotone linesearch procedure is introduced, which is combined with the Broyden's class. Un...
The Global Convergence of Self-scale BFGS Algorithm with Nonmonotone Line Search for Unconstrained Nonconvex Optimization Problems
nonmonotone line search self-scaling BFGS method global convergence
2007/12/11
The self-scaling quasi-Newton method solves an unconstrained optimization problem by scaling the Hessian approximation matrix before it is updated at each iteration to avoid the possible large eigenva...
This paper presents a new conjugate gradient method for unconstrained optimization. This method reduces to the Polak-Ribiere-Polyak method when line searches are exact. But their performances are diff...
GLOBAL CONVERGENCE OF UNCONSTRAINED MINIMIZATION METHODS WITH A GENERALIZED BACKTRACKING LINESEARCH PROCEDURE
Backtracking linesearch direction selec
2007/8/7
This paper presents a generalized backtracking linesearch procedure, which includes the backtracking linesearch and many other linesearches. Under very mild conditions we show the global convergence o...
Global Convergence for Discrete Dynamical Systems and Forward Neural Networks
Discrete Dynamical Systems Forward Neural Networks
2010/3/1
Using a theoretical result regarding the global stability of discrete dynamical systems of lower triangular form, we establish convergence properties of forward neural networks when the neuron respons...