This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...
This paper addresses the problem of selecting the `optimal' variable subset in a logistic regression model for a medium-sized data set. As a case study, we take the British En...
We introduce a distributed hash table (DHT) with logarithmic degree and logarithmic dilation. We show two lookup algorithms. The first has a message complexity of log n and is ro...
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
This paper develops procedures for selecting a set of normal populations with unknown means and unknown variances in order that the final subset of selected populations satisfies ...