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Central Limit Theorems and Large Deviations for Additive Functionals of Reflecting Diffusion Processes
Central Limit Theorems Large Deviations Additive Functionals Reflecting Diffusion Processes
2015/7/6
This paper develops central limit theorems (CLT's) and large deviations results for additive functionals associated with reflecting disions in which the functional may include a term associated with t...
Analysis of a Stochastic Approximation Algorithm for Computing Quasi-stationary Distributions
Stochastic approximations quasi-stationary distribution ODE method.
2015/7/6
This paper analyzes the convergence properties of an iterative Monte Carlo procedure proposed in the Physics literature for estimating the quasi-stationary distribution on a transient set of a Markov ...
By dark of night they howl across Delaware Bay, these winds that reach 60 miles per hour. The gales of a nor'easter in May—a winter storm that happens this late in the season only once a century—overt...
Educating for Identity: Problematizing and Deconstructing Our Literacy Pasts
Problematizing Deconstructing
2015/7/3
In order to become effective teachers of language and literacy, it is critical for teacher
candidates to have a sense of who they are as literate beings, how their literacy pasts have been
lived, ...
Novel 1 H low field nuclear magnetic resonance applications for the field of biodiesel
magnetic resonance field nuclear
2015/7/3
Biodiesel production has increased dramatically over the last decade, raising the need for new rapid
and non-destructive analytical tools and technologies. 1
H Low Field Nuclear Magnetic Resonance (...
USER’S GUIDE FOR QPOPT 1.0: A FORTRAN PACKAGE FOR QUADRATIC PROGRAMMING
Quadratic programming linear programming linear constraints
2015/7/3
QPOPT is a set of Fortran subroutines for minimizing a general quadratic function
subject to linear constraints and simple upper and lower bounds. QPOPT may also be
used for linear programming and f...
SOLVING REGULARIZED LINEAR PROGRAMS USING BARRIER METHODS AND KKT SYSTEMS
barrier methods interior methods linear programming
2015/7/3
We discuss the solution of regularized linear programs using a primal-dual barrier
method. Our implementation is based on indeˉnite Cholesky-type factorizations of full and reduced
KKT systems. Regu...
User’s Guide for SNOPT Version 7: Software for Large-Scale Nonlinear Programming
optimization large-scale nonlinear programming nonlinear constraints
2015/7/3
SNOPT is a general-purpose system for constrained optimization. It minimizes a
linear or nonlinear function subject to bounds on the variables and sparse linear or
nonlinear constraints. It is suita...
SOLUTION OF SPARSE LINEAR EQUATIONS USING CHOLESKY FACTORS OF AUGMENTED SYSTEMS
sparse linear equations direct methods unsymmetric matrices
2015/7/3
Cholesky factorizations have reached a high peak of e±ciency for solving sparse
symmetric systems, largely because their Analyze and Factor phases do not con°ict. We explore the
possibility of using...
The time-frequency and time-scale communities have recently developed a large number of
overcomplete waveform dictionaries—stationary wavelets, wavelet packets, cosine packets,
chirplets, and warple...
The lasso penalizes a least squares regression by the sum of the absolute values
(L1-norm) of the coefficients. The form of this penalty encourages sparse solutions (with many
coefficien...
A GLOBALLY CONVERGENT LINEARLY CONSTRAINED LAGRANGIAN METHOD FOR NONLINEAR OPTIMIZATION
large-scale optimization nonlinear programming
2015/7/3
The new algorithm has been implemented in Matlab, with an option to use either MINOS or
SNOPT (Fortran codes) to solve the linearly constrained subproblems. Only first derivatives are
required...
Stable and efficient updates to the basis matrix factors are vital to the simplex
method. The "best" updating method depends on the machine in use and how the update is implemented. For example, the ...
PRECONDITIONERS FOR INDEFINITE SYSTEMS ARISING IN OPTIMIZATION
indefinite systems preconditioners linear programming
2015/7/3
Methods are discussed for the solution of sparse linear equations Ky z, where K is
symmetric and indefinite. Since exact solutions are not always required, direct and iterative methods
are both of i...
LEAST SQUARES ESTIMATION OF DISCRETE LINEAR DYNAMIC SYSTEMS USING ORTHOGONAL TRANSFORMATIONS
DISCRETE LINEAR DYNAMIC SYSTEMS ORTHOGONAL TRANSFORMATIONS
2015/7/3
Kalman [9] introduced a method for estimating the state of a discrete linear dynamic
system subject to noise. His method is fast but has poor numerical properties. Duncan and Horn [3]
showed that th...