We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a ...
Tamar Kushnir, Alison Gopnik, Chris Lucas, Laura S...
Abstract. The recovery of the mixture of an N-dimensional signal generated by N independent processes is a well studied problem (see e.g. [1,10]) and robust algorithms that solve t...
Harold W. Gutch, Takanori Maehara, Fabian J. Theis
How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, biology and medicine. Existing ...
Share-frequent pattern mining discovers more useful and realistic knowledge from database compared to the traditional frequent pattern mining by considering the non-binary frequen...
The present paper deals with the learnability of indexed families of uniformly recursive languages from positive data as well as from both, positive and negative data. We consider...