We address the challenge of assessing conservation of gene expression in complex, non-homogeneous datasets. Recent studies have demonstrated the success of probabilistic models in...
We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
Sequential optimal design methods hold great promise for improving the efficiency of neurophysiology experiments. However, previous methods for optimal experimental design have in...
Jeremy Lewi, Robert J. Butera, David M. Schneider,...
Consider data consisting of pairwise measurements, such as presence or absence of links between pairs of objects. These data arise, for instance, in the analysis of protein intera...
Edoardo Airoldi, David M. Blei, Stephen E. Fienber...
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...