Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
In this paper, we present an extension of PHIL, a declarative language for filtering information from XML data. The proposed approach allows us to extract relevant data as well a...
Abstract— Particle filters have been applied with great success to various state estimation problems in robotics. However, particle filters often require extensive parameter tw...
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
We consider the filter decomposition problem in supporting coarse-grained pipelined parallelism. This form of parallelism is suitable for data-driven applications in scenarios wh...