Unlike today’s reactive approaches, information flow based approaches can provide positive assurances about overall system integrity, and hence can defend against sophisticated...
Weiqing Sun, R. Sekar, Gaurav Poothia, Tejas Karan...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
The problem of generating referring expressions (GRE) is an important task in natural language generation. In this paper, we advocate for the use of logical languages in the output...
Carlos Areces, Santiago Figueira, Daniel Gor&iacut...
Ambiguity in the output is a concern for NLG in general. This paper considers the case of structural ambiguity in spoken language generation. We present an algorithm which inserts ...
We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail we are given a set ...