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Much of modern data processing requires identification of low-dimensional structures in high-dimensional spaces, using observations that are incomplete or noisy. This general paradigm applies to the restoration of images (where natural images form a low-dimensional subset of the space of … Read More

Much of modern data processing requires identification of low-dimensional structures in high-dimensional spaces, using observations that are incomplete or noisy. This general paradigm applies to the restoration of images (where natural images form a low-dimensional subset of the space of … Read More

Convex optimisation and stochastic sampling are two powerful methodologies for performing statistical inference in inverse problems related to signal and image processing. It is widely acknowledged that these methodologies can complement each other very well; yet they are generally studied … Read More

Jet engines rank amongst the most complex machines ever built and are governed by deterministic and stochastic phenomena. Since jet engines are subject to extremely demanding operating conditions, a proper maintenance is critical to ensure high safety, maximum availability and … Read More

We address the representation of two-dimensional shapes in its most general form, i.e., arbitrary sets of points. Examples of these shapes arise in multiple situations, in the form of sparse sets of representative landmarks, or dense sets of image edge … Read More

Evolutionary algorithms are stochastic optimization techniques based on the principles of natural evolution, and Genetic Programming (GP) belongs to this family. In recent years the study of GP systems has been extended to phenotypic aspects, while previously it was mainly … Read More

The performance of non-invasive electroencephalogram-based (EEG) brain–computer interfaces (BCIs) has improved significantly in recent years. However, remaining challenges include the non-stationarity and the low signal-to-noise ratio of the EEG, which limit the bandwidth and hence the available applications. Optimization of … Read More

Melanoma (skin cancer) is considered one of the most concerning forms of cancer due to its great potential to metastasize. Furthermore, statistical data show that the incidence rates of melanoma have been steadily growing in the past decades, leading to … Read More

In the first part of this talk, I will present AD^3 (Alternating Direction Dual Decomposition), a new decoding algorithm for approximate LP-MAP inference in constrained factor graphs. The LP-MAP approximation consists in ignoring global effects caused by the cycles of … Read More

The structure control system design consists mainly of two steps: input/output (I/O) selection and control configuration (CC) selection. The first one is devoted to the problem of computing how many actuators/sensors are needed and where should be placed in the … Read More