Learning through failure

TitleLearning through failure
Publication TypeJournal Articles
Year of Publication2006
AuthorsSato T, Kameya Y, De Raedt L, Dietterich T, Getoor L, Muggleton SH
JournalProbabilistic, Logical and Relational Learning-Towards a Synthesis
Issue05051
Date Published2006///
Abstract

PRISM, a symbolic-statistical modeling language we have been developing since '97, recently incorporated a program transformation technique to handle failure in generative modeling. I'll show this feature opens a way to new breeds of symbolic models, including EM learning from negative observations, constrained HMMs and finite PCFGs.