## Search

Now showing items 11-20 of 35

#### 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. ...

#### Survival-Time Classi cation of Breast Cancer Patients

(2001)

The identi cation of breast cancer patients for whom chemother-
apy could prolong survival time is treated here as a data mining prob-
lem. This identi cation is achieved by clustering 253 breast cancer
patients into ...

#### 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 ...

#### Robust Linear and Support Vector Regression

(2000-09)

The robust Huber M-estimator, a differentiable cost function that is quadratic for small errors and linear otherwise, is
modeled exactly, in the original primal space of the problem, by an easily solvable simple convex ...

#### Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels

(2007)

We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose
input feature columns are divided into groups belonging to different entities. Each entity is unwilling to share
its ...

#### Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels

(2007)

We propose a novel privacy-preserving nonlinear support vector machine (SVM) classifier for a
data matrix A whose columns represent input space features and whose individual rows are divided
into groups of rows. Each ...

#### 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 ...

#### Nonlinear Knowledge in Kernel Approximation

(2006)

Prior knowledge over arbitrary general sets is
incorporated into nonlinear kernel approximation problems in
the form of linear constraints in a linear program. The key
tool in this incorporation is a theorem of the ...