Modern software must evolve in response to changing conditions. In the most widely used programming environments, code is static and cannot change at runtime. This poses problems ...
Scott Malabarba, Raju Pandey, Jeff Gragg, Earl T. ...
Abstract. We apply a machine learning method to the occupation coding, which is a task to categorize the answers to open-ended questions regarding the respondent’s occupation. Sp...
This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...