Now showing items 1-10 of 10

    • Breast Tumor Susceptibility to Chemotherapy via Support Vector Machines 

      Mangasarian, Olvi; Fung, Glenn (2003)
      Support vector machines (SVMs), utilizing RNA signature measurements, were used to generate a classi er to distinguish breast cancer patients that are partial-responders to chemotherapy treatment, from patients that are ...
    • Data Selection for Support Vector Machine Classifiers 

      Olvi, Mangasarian; Fung, Glenn (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 ...
    • Equivalence of Minimal L0 and Lp Norm Solutions of Linear Equalities, Inequalities and Linear Programs for Sufficiently Small p 

      Mangasarian, Olvi; Fung, Glenn (2011)
      For a bounded system of linear equalities and inequalities we show that the NP-hard ?0 norm minimization problem min ||x||0 subject to Ax = a, Bx ? b and ||x||? ? 1, is completely equivalent to the concave minimization ...
    • Finite Newton Method for Lagrangian Support Vector Machine Classi cation 

      Mangasarian, Olvi; Fung, Glenn (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 ...
    • Incremental Support Vector Machine Classi cation 

      Mangasarian, Olvi; Fung, Glenn (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 ...
    • Knowledge-Based Nonlinear Kernel Classi ers 

      Shavlik, Jude; Mangasarian, Olvi; Fung, Glenn (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 ...
    • Knowledge-Based Support Vector Machine Classi ers 

      Shavlik, Jude; Mangasarian, Olvi; Fung, Glenn (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 ...
    • Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels 

      Fung, Glenn; Wild, Edward; Mangasarian, Olvi (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 Linear and Nonlinear Approximation via Linear Programming 

      Mangasarian, Olvi; Fung, Glenn (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 ...
    • Proximal Knowledge-Based Classification 

      Fung, Glenn; Wild, Edward; Mangasarian, Olvi (2008-06-26)
      Prior knowledge over general nonlinear sets is incor- porated into proximal nonlinear kernel classification problems as linear equalities. The key tool in this incorporation is the conversion of general nonlinear prior ...