Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
The authors propose a general theoretical framework for structured prediction that deals with cases where the data exhibits a local structure, so that the inputs and outputs can be decomposed into parts. The paper analyses the new framework theoretically and empirically. The reviewers deemed the theoretical contributions to be of original and of a high quality. The author response addressed the perceived weaknesses, in particular in the empirical evaluation, in a satisfcatory way.