Browsing DMI Technical Reports by Issue Date
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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 ... 
Large Scale Kernel Regression via Linear Programming
(1999)The problem of tolerant data tting by a nonlinear surface, in duced by a kernelbased support vector machine [24], is formulated as a linear program with fewer number of variables than that of other linear programming ... 
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 ... 
Optimization of Gamma Knife Radiosurgery
(2000)The Gamma Knife is a highly specialized treatment unit that pro vides an advanced stereotactic approach to the treatment of tumors, vascular malformations, and pain disorders within the head. Inside a shielded ... 
FATCOP 2.0: Advanced Features in an Opportunistic Mixed Integer Programming Solver
(2000)We describe FATCOP 2.0, a new parallel mixed integer program solver that works in an opportunistic computing environment provided by the Condor resource management system. We outline changes to the search strategy of ... 
A Practical Approach to Samplepath Simulation Optimization
(2000)We propose solving continuous parametric simulation optimizations using a deterministic nonlinear optimiza tion algorithm and samplepath simulations. The op timization problem is written in a modeling language with ... 
Data Selection for Support Vector Machine Classifiers
(2000)The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classi er, is formulated as a concave minimization problem and solved by a nite number ... 
Interior Point Methods for Massive Support Vector Machines
(20000525)We investigate the use of interior point methods for solving quadratic programming problems with a small number of linear constraints where the quadratic term consists of a lowrank update to a positive semide nite matrix. ... 
Robust Linear and Support Vector Regression
(200009)The robust Huber Mestimator, 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 ... 
Semismooth Support Vector Machines
(20001129)The linear support vector machine can be posed as a quadratic pro gram in a variety of ways. In this paper, we look at a formulation using the twonorm for the misclassi cation error that leads to a positive de  nite ... 
Slice Models in General Purpose Modeling Systems
(20001214)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 crossvalidation, ... 
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 ... 
SurvivalTime 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 ... 
CrossValidation, Support Vector Machines and Slice Models
(2001)We show how to implement the crossvalidation technique used in ma chine learning as a slice model. We describe the formulation in terms of support vector machines and extend the GAMS/DEA interface to allow for e cient ... 
A Finite Newton Method for Classi cation Problems
(2001)A fundamental classi cation problem of data mining and machine learning is that of minimizing a strongly convex, piecewise quadratic function on the ndimensional real space Rn. We show nite termination of a Newton ... 
KnowledgeBased 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 ... 
Set Containment Characterization
(2001)Characterization of the containment of a polyhedral set in a closed halfspace, a key factor in generating knowledgebased support vector machine classi ers [7], is extended to the following: (i) Containment of one ... 
Data Mining via Support Vector Machines
(2001)Support vector machines (SVMs) have played a key role in broad classes of problems arising in various elds. Much more recently, SVMs have become the tool of choice for problems arising in data classi  cation and mining. ... 
SIMULATION OPTIMIZATION BASED ON A HETEROGENEOUS COMPUTING ENVIRONMENT
(2001)We solve a simulation optimization using a deterministic nonlinear solver based on the samplepath concept. The method used a quadratic model built from a collection of surrounding simulation points. The scheme does not ... 
RSVM: Reduced Support Vector Machines
(200101)An algorithm is proposed which generates a nonlinear kernelbased separating surface that requires as little as 1% of a large dataset for its explicit evaluation. To generate this nonlinear surface, the entire dataset ...