This paper proposes an alternative definition of elementary loops and extends the notion of proper loops for disjunctive logic programs. Different from normal logic programs, the...
One key challenge in statistical relational learning (SRL) is scalable inference. Unfortunately, most realworld problems in SRL have expressive models that translate into large gr...
Mohamed Hamza Ibrahim, Christopher J. Pal, Gilles ...
Programmers are loathe to interrupt their workflow to document their design rationale, leading to frequent errors when software is modified—often much later and by different p...
The Web contains a large amount of information in the form of videos that remains inaccessible to the visually impaired people. We identify a class of videos whose information con...
The paper presents an approach for optimizing the evaluation of SPARQL queries over OWL ontologies using SPARQL’s OWL Direct Semantics entailment regime. The approach is based o...
In this paper, we consider the problem of energy disaggregation, i.e., decomposing a whole home electricity signal into its component appliances. We propose a new supervised algor...
Autoregressive moving average (ARMA) models are a fundamental tool in time series analysis that offer intuitive modeling capability and efficient predictors. Unfortunately, the l...
Martha White, Junfeng Wen, Michael Bowling, Dale S...
Querying inconsistent ontologies is an intriguing new problem that gave rise to a flourishing research activity in the description logic (DL) community. The computational complexi...
Thomas Lukasiewicz, Maria Vanina Martinez, Andreas...
Most typical statistical and machine learning approaches to time series modeling optimize a singlestep prediction error. In multiple-step simulation, the learned model is iterativ...
Arun Venkatraman, Martial Hebert, J. Andrew Bagnel...
We present an approach to incorporate interesting and compelling characters in planning-based narrative generation. The approach is based on a computational model that utilizes ch...