Learn More
This paper addresses the making of security decisions, such as access-control decisions or spam filtering decisions, under uncertainty, when the benefit of doing so outweighs the need to absolutely guarantee these decisions are correct. For instance, when there are limited, costly, or failed communication channels to a policy-decision-point. Previously,(More)
The Grid is a concept which allows the sharing of resources between distributed communities, allowing each to progress towards potentially different goals. As adoption of the Grid increases so are the activities that people wish to conduct through it. The GRIDCC project is a European Union funded project addressing the issues of integrating instruments into(More)
1 Motivation and contributions In this paper, we address a specific use-case of wearable or hand-held camera technology: indoor navigation. We explore the possibility of crowdsourcing navigational data in the form of video sequences that are captured from wearable or hand-held cameras. Without using geometric inference techniques (such as SLAM), we test(More)
Privacy violations in online social networks (OSNs) often arise as a result of users sharing information with unintended audiences. One reason for this is that, although OSN capabilities for creating and managing social groups can make it easier to be selective about recipients of a given post, they do not provide enough guidance to the users to make(More)
— An understanding of information flow has many applications, including for maximising marketing impact on social media, limiting malware propagation, and managing un-desired disclosure of sensitive information. This paper presents scalable methods for both learning models of information flow in networks from data, based on the Independent Cascade Model;(More)
Probabilistic logic programming has traditionally focused on languages where probabilities or weights are specified or inferred directly, rather than through Bayesian priors. To address this limitation, we propose a probabilistic logic programming language that bridges the gap between logical and probabilistic inference in categorical models with Dirichlet(More)