## Search

Now showing items 1-7 of 7

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

(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, ...

#### Sparse Representations of Multiple Signals

(1997-09-01)

We discuss the problem of finding sparse representations of a class of signals. We formalize the problem and prove it is NP-complete both in the case of a single signal and that of multiple ones. Next we develop a simple ...

#### A Note on the Generalization Performance of Kernel Classifiers with Margin

(2000-05-01)

We present distribution independent bounds on the generalization misclassification performance of a family of kernel classifiers with margin. Support Vector Machine classifiers (SVM) stem out of this class of machines. The ...

#### Image-Based View Synthesis

(1997-01-01)

We present a new method for rendering novel images of flexible 3D objects from a small number of example images in correspondence. The strength of the method is the ability to synthesize images whose viewing position ...

#### Image Based Rendering Using Algebraic Techniques

(1996-11-01)

This paper presents an image-based rendering system using algebraic relations between different views of an object. The system uses pictures of an object taken from known positions. Given three such images it can ...

#### From Regression to Classification in Support Vector Machines

(1998-11-01)

We study the relation between support vector machines (SVMs) for regression (SVMR) and SVM for classification (SVMC). We show that for a given SVMC solution there exists a SVMR solution which is equivalent for a certain ...

#### A Unified Framework for Regularization Networks and Support Vector Machines

(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 ...