Schlumberger RPS successfully applies software measurement to support their software development projects. It is proposed that the success of their measurement practices is mainly...
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
Abstract. We present a new learning to rank framework for estimating context-sensitive term weights without use of feedback. Specifically, knowledge of effective term weights on ...
This paper proposes extending semi-supervised learning by allowing an ongoing interaction between a user and the system. The extension is intended to not only to speed up search fo...
We present new fingerprint classification algorithms based on two machine learning approaches: support vector machines (SVMs), and recursive neural networks (RNNs). RNNs are traine...
Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil...