Now showing items 54-64 of 64

• Segmentation of Pulmonary Nodule Images Using Total Variation Minimization ﻿

(Cornell University, 2003-01-22)
Total variation minimization has edge preserving and enhancing properties which make it suitable for image segmentation. We present Image Simplification, a new formulation and algorithm for image segmentation. We illustrate ...
• Segmentation of Pulmonary Nodule Images Using Total VariationMinimization ﻿

(Cornell University, 1998-09)
Total variation minimization has edge preserving and enhancing properties which make it suitable for image segmentation. We present Image Simplification, a new formulation and algo rithm for image segmentation. We ...
• Software For Estimating Sparse Hessian Matrices ﻿

(Cornell University, 1985-01)
The solution of a nonlinear optimization problem often requires an estimate of the Hessian matrix for a function $f$. In large scale problems the Hessian matrix is usually sparse, and then estimation by differences of ...
• Software for Estimating Sparse Jacobian Matrices ﻿

(Cornell University, 1982-06)
In many nonlinear problems it is necessary to estimate the Jacobian matrix of a nonlinear mapping $F$. In large scale problems the Jacobian of $F$ is usually sparse, and then estimation by differences is attractive because ...
• Solution of Nonlinear Least-Square Problems on a Multiprocessor ﻿

(Cornell University, 1988-06)
In this paper we describe algorithms for solving nonlinear least-squares problems on a message-passing multiprocessor. We demonstrate new parallel algorithms, including an efficient parallel algorithm for determining the ...
• Solving Systems of Nonlinear Equations on a Message-Passing Multiprocessor ﻿

(Cornell University, 1987-11)
We develop parallel algorithms for the solution of dense systems of nonlinear equations on a message-passing multiprocessor computer. Specifically, we propose a distributed finite-difference Newton method, a multiple ...
• The Sparse Null Space Basis Problem ﻿

(Cornell University, 1984-07)
The sparse null space basis problem is the following: $A t \times n$ matrix $A (t less than n)$ is given. Find a matrix $N$, with the fewest nonzero entries in it, whose columns span the null space of $A$. This problem ...
• Structure and Efficient Hessian Calculation ﻿

(Cornell University, 1996-08)
Modern methods for numerical optimization calculate (or approximate) the matrix of second derivatives, the Hessian matrix, at each iteration. The recent arrival of robust software for automatic differentiation allows for ...
• Structure and Efficient Jacobian Calculation ﻿

(Cornell University, 1996-03)
Many computational tasks require the determination of the Jacobian matrix, at a given argument, for a large nonlinear system of equations. Calculation or approximation of a Newton step is a related task. The development ...
• A Subspace, Interior, and Conjugate Gradient Method for Large-scale Bound-constrained Minimization Problems ﻿

(Cornell University, 1995-07)
A subspace adaption of the Coleman-Li trust region and interior method is proposed for solving large-scale bound-constrained minimization problems. This method can be implemented with either sparse Cholesky factorization ...
• A Subspace, Interior, and Conjugate Gradient Method for Large-ScaleBound-Constrained Minimization Problems ﻿

(Cornell University, 1995-07)
A subspace adaptation of the Coleman-Li trust region and interior method is proposed for solving large-scale bound-constrained minimization problems. This method can be implemented with either sparse Cholesky factorization ...