We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by rem...
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
We investigate a topic at the interface of machine learning and cognitive science. Human active learning, where learners can actively query the world for information, is contraste...
Rui M. Castro, Charles Kalish, Robert Nowak, Ruich...
We present the results of a large-scale, end-to-end human evaluation of various sentiment summarization models. The evaluation shows that users have a strong preference for summar...
Kevin Lerman, Sasha Blair-Goldensohn, Ryan T. McDo...
For transmission of continuous media (CM) streams such as audio and video over the Internet, a critical issue is that periodic network overloads cause bursty packet losses. Studie...