We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand data by discovering useful ...
Michael J. Pazzani, Subramani Mani, William Rodman...
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...