Browsing DMI Technical Reports by Title
Now showing items 1433 of 46

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 ... 
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. ... 
KnowledgeBased 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 ... 
KnowledgeBased Nonlinear Kernel Classi ers
(2003)Prior knowledge in the form of multiple polyhedral sets, each belonging to one of two categories, is introduced into a reformulation of a nonlinear kernel support vector machine (SVM) classi er. The resulting formulation ... 
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 ... 
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 ... 
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 ... 
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 ... 
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 ... 
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 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 ... 
Nonlinear KnowledgeBased 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 ... 
An optimization approach for radiosurgery treatment planning
(20011106)We outline a new approach for radiosurgery treatment planning, based on solving a series of optimization problems. We consider a speci c treat ment planning problem for a specialized device known as the Gamma Knife, ... 
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 ... 
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 ... 
PrimalDual Bilinear Programming Solution of the Absolute Value Equation
(2011)We propose a finitely terminating primaldual bilinear programming algorithm for the solution of the NPhard absolute value equation (AVE): Ax ? x = b, where A is an n � n square matrix. The algorithm, which makes no ... 
PrivacyPreserving Classification of Horizontally Partitioned Data via Random Kernels
(2007)We propose a novel privacypreserving 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 ... 
PrivacyPreserving Classification of Vertically Partitioned Data via Random Kernels
(2007)We propose a novel privacypreserving 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 ... 
PrivacyPreserving Horizontally Partitioned Linear Programs
(2010)We propose a simple privacypreserving reformulation of a linear program whose equality constraint matrix is partitioned into groups of rows. Each group of matrix rows and its corresponding right hand side vector are ... 
PrivacyPreserving Linear and Nonlinear Approximation via Linear Programming
(2011)We propose a novel privacypreserving 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 ...