Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
In an 2D echocardiogram exam, an ultrasound probe
samples the heart with 2D slices. Changing the orientation
and position on the probe changes the slice viewpoint, altering
the ...
Ritwik Kumar, Fei Wang, David Beymer, Tanveer Fath...
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...