## Search

Now showing items 1-10 of 16

#### Exactness Conditions for a Convex Differentiable Exterior Penalty for Linear Programming

(2007)

Sufficient conditions are given for a classical dual exterior penalty
function of a linear program to be independent of its penalty parameter.
This ensures that an exact solution to the primal linear program can be
obtained ...

#### Privacy-Preserving Linear and Nonlinear Approximation via Linear Programming

(2011)

We propose a novel privacy-preserving random kernel approximation based on a data matrix
A ? Rm�n whose rows are divided into privately owned blocks. Each block of rows belongs to
a different entity that is unwilling to ...

#### Primal-Dual Bilinear Programming Solution of the Absolute Value Equation

(2011)

We propose a finitely terminating primal-dual bilinear programming algorithm for the solution of
the NP-hard absolute value equation (AVE): Ax ? |x| = b, where A is an n � n square matrix. The
algorithm, which makes no ...

#### A Newton Method for Linear Programming

(2002)

A fast Newton method is proposed for solving linear programs with
a very large ( 106) number of constraints and a moderate ( 102)
number of variables. Such linear programs occur in data mining and
machine learning. ...

#### Nonlinear Knowledge-Based Classification

(2006)

Prior knowledge over general nonlinear sets is incorporated into nonlinear kernel classification
problems as linear constraints in a linear program. The key tool in this incorporation is a theorem
of the alternative for ...

#### Knowledge-Based Linear Programming

(2003)

We introduce a class of linear programs with constraints in the form
of implications. Such linear programs arise in support vector machine
classi cation, where in addition to explicit datasets to be classi ed, prior
knowledge ...

#### Chunking for Massive Nonlinear Kernel Classification

(2006)

A chunking procedure [2] utilized in [18] for linear classifiers is proposed here for nonlinear kernel
classification of massive datasets. A highly accurate algorithm based on nonlinear support vector
machines that ...

#### Support Vector Machine Classi cation via Parameterless Robust Linear Programming

(2003)

We show that the problem of minimizing the sum of arbitrary-norm
real distances to misclassi ed points, from a pair of parallel bounding
planes of a classi cation problem, divided by the margin (distance) be-
tween the ...

#### Large Scale Kernel Regression via Linear Programming

(1999)

The problem of tolerant data tting by a nonlinear surface, in-
duced by a kernel-based support vector machine [24], is formulated as
a linear program with fewer number of variables than that of other
linear programming ...

#### Knowledge-Based Support Vector Machine Classi ers

(2001)

Prior knowledge in the form of multiple polyhedral sets, each belonging
to one of two categories, is introduced into a reformulation
of a linear support vector machine classi er. The resulting formulation
leads to a ...