Now showing items 28-30 of 123

    • On the V(subscript gamma) Dimension for Regression in Reproducing Kernel Hilbert Spaces 

      Evgeniou, Theodoros; Pontil, Massimiliano (1999-05-01)
      This paper presents a computation of the $V_gamma$ dimension for regression in bounded subspaces of Reproducing Kernel Hilbert Spaces (RKHS) for the Support Vector Machine (SVM) regression $epsilon$-insensitive loss function, ...
    • A Unified Framework for Regularization Networks and Support Vector Machines 

      Evgeniou, Theodoros; Pontil, Massimiliano; Poggio, Tomaso (1999-03-01)
      Regularization Networks and Support Vector Machines are techniques for solving certain problems of learning from examples -- in particular the regression problem of approximating a multivariate function from sparse ...
    • Multivariate Density Estimation: An SVM Approach 

      Mukherjee, Sayan; Vapnik, Vladimir (1999-04-01)
      We formulate density estimation as an inverse operator problem. We then use convergence results of empirical distribution functions to true distribution functions to develop an algorithm for multivariate density estimation. ...