## Search

Now showing items 1-10 of 46

#### Lagrangian Support Vector Machines

(2000)

An implicit Lagrangian for the dual of a simple reformulation of
the standard quadratic program of a linear support vector machine
is proposed. This leads to the minimization of an unconstrained
di erentiable convex ...

#### Multiple Instance Classification via Successive Linear Programming

(2005)

The multiple instance classification problem [6,2,12] is formulated using a linear
or nonlinear kernel as the minimization of a linear function in a finite dimensional
(noninteger) real space subject to linear and bilinear ...

#### Massive Data Classification via Unconstrained Support Vector Machines

(2006)

A highly accurate algorithm, based on support vector machines
formulated as linear programs [13, 1], is proposed
here as a completely unconstrained minimization problem
[15]. Combined with a chunking procedure [2] this ...

#### Slice Models in General Purpose Modeling Systems

(2000-12-14)

Slice models are collections of mathematical programs with the same
structure but di erent data. Examples of slice models appear in Data
Envelopment Analysis, where they are used to evaluate e ciency, and
cross-validation, ...

#### Finite Newton Method for Lagrangian Support Vector Machine Classi cation

(2002)

An implicit Lagrangian [19] formulation of a support vector machine
classi er that led to a highly e ective iterative scheme [18] is
solved here by a nite Newton method. The proposed method, which
is extremely fast and ...

#### SSVM: A Amooth Support Vector Machine for Classification

(1999)

Smoothing methods, extensively used for solving important math-
ematical programming problems and applications, are applied here
to generate and solve an unconstrained smooth reformulation of the
support vector machine ...

#### RSVM: Reduced Support Vector Machines

(2001-01)

An algorithm is proposed which generates a nonlinear kernel-based
separating surface that requires as little as 1% of a large dataset for its explicit
evaluation. To generate this nonlinear surface, the entire dataset ...

#### 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 ...

#### Feature Selection in k-Median Clustering

(2004)

An e ective method for selecting features in clustering
unlabeled data is proposed based on changing the objective
function of the standard k-median clustering algorithm. The
change consists of perturbing the objective ...

#### Incremental Support Vector Machine Classi cation

(2001)

Using a recently introduced proximal support vector ma-
chine classi er [4], a very fast and simple incremental support vector
machine (SVM) classi er is proposed which is capable of modifying an
existing linear classi ...