We present a new method for regularized convex optimization and analyze it under both online and stochastic optimization settings. In addition to unifying previously known firstor...
John Duchi, Shai Shalev-Shwartz, Yoram Singer, Amb...
In high-dimensional classification problems it is infeasible to include enough training samples to cover the class regions densely. Irregularities in the resulting sparse sample d...
The usual data mining setting uses the full amount of data to derive patterns for different purposes. Taking cues from machine learning techniques, we explore ways to divide the d...
A number of two-class classification methods first discretize each attribute of two given training sets and then construct a propositional DNF formula that evaluates to True for ...
At the International Research and Educational Institute for Integrated Medical Sciences (IREIIMS) project, we are collecting complete medical data sets to determine relationships b...