This paper explores how information that is usually discarded during a step of the transformation of a high-level program into a binary executable in a modern toolchain could be used in the consecutive steps. It is shown that by retaining the “big picture” even at the lower levels of abstraction a program can be both more efficient and easier to debug. Methods are discussed how to propagate thi...

Automatic generalization is a process for representing geographical objects with different degrees of detail on a digital map. The positional error for each geographical object is propagated through the process and a generalization error is also introduced by the generalization. Previous research has focused mainly on measuring the generalization error. This paper presents an analytical model f...

This paper proposes a new Information Retrieval Model based on possibility and necessity measures. This model encodes relationship dependencies existing between terms, documents and query by possibilistic networks. The user’s query triggers a propagation process to retrieve necessarily or at least possibly relevant documents.

A goal in Vehicular Ad hoc Networks (VANETs) is to enable the dissemination of traffic and road conditions such as local congestion and surface ice as detected by independently moving vehicles. This activity known as Information Warning Functions is useful for vehicles on the highway and enables early reaction. This problem can be described as the directional propagation of information originat...

We show that excitations of interacting quantum particles in lattice models – and thus information in these systems – always propagate with a finite speed of sound. Our argument is simple yet general and shows that by focusing on the physically relevant observables one can typically expect a bounded speed of information propagation. It applies equally to quantum spins, bosons such as in the Bos...

Online users nowadays are facing serious information overload problem. In recent years, recommender systems have been widely studied to help people find relevant information. Adaptive social recommendation is one of these systems in which the connections in the online social networks are optimized for the information propagation so that users can receive interesting news or stories from their l...

Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural re...

Networks provide a ‘skeleton’ for the spread of contagions, like, information, ideas, behaviors and diseases. Many times networks over which contagions diffuse are unobserved and need to be inferred. Here we apply survival theory to develop general additive and multiplicative risk models under which the network inference problems can be solved efficiently by exploiting their convexity. Our addi...