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Processing of electroencephalographic (EEG) signals has mostly focused on analysing correlates that are time-locked to an observable event. However, when the signal is acquired in less controlled environment, like in the context of a brain-computer interfa ...
This paper introduces a simple, general framework for likelihood-free Bayesian reinforcement learning, through Approximate Bayesian Computation (ABC). The main advantage is that we only require a prior distribution on a class of simulators (generative mode ...
This paper introduces a computer-based training program for enhancing numerical cognition aimed at children with developmental dyscalculia. Through modelling cognitive processes and controlling the level of their stimulation, the system optimizes the learn ...
Latent class models are a convenient and intuitive way to introduce taste heterogeneity in discrete choice models by relating attributes of the decision makers with unobserved behavioral classes, hence allowing for a more accurate market segmentation. Esti ...
View synthesis prediction (VSP) is a coding mode that predicts video blocks from synthesised frames. It is particularly useful in a multi-camera setup with large inter-camera distances. Adding a VSP-based SKIP mode to a standard Multiview Video Coding (MVC ...
Institute of Electrical and Electronics Engineers2013
The issue of Coverage in visual sensor networks (VSNs) has attracted considerable attention due to sensors unique directional sensing characteristic. It answers the question that how well the target field is monitored by a network of sensors with video/ima ...
Many applications in machine learning require optimizing unknown functions defined over a high-dimensional space from noisy samples that are expensive to obtain. We address this notoriously hard challenge, under the assumptions that the function varies onl ...
Statistics of spatial extremes is developing very rapidly, owing to the demands of applications in the environmental sciences and the insurance and risk industries. This entry sketches the main ideas, based on classical extreme-value statistics. The two ma ...
In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of cont ...
Probabilistic matrix factorization methods aim to extract meaningful correlation structure from an incomplete data matrix by postulating low rank constraints. Recently, variational Bayesian (VB) inference techniques have successfully been applied to such l ...