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Geometric and combinatorial foundations for emerging information and inference s...

Geometric and combinatorial foundations for emerging information and inference systems Recent developments in sensor technology, robotics, communications, signal, and semantic processing and computation have enabled the emergence of new information and inference systems (IIS) within the Information and Communication... ver más

31/10/2014

EPFL

100K€

Presupuesto del proyecto: 100K€

Líder del proyecto

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2014-10-31 No tenemos la información de la convocatoria

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No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

EPFL

0.00€ | Lider

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Líder del proyecto

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 100K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Recent developments in sensor technology, robotics, communications, signal, and semantic processing and computation have enabled the emergence of new information and inference systems (IIS) within the Information and Communications Technologies umbrella of the Seventh Network Program that accomplish automatic reasoning tasks using a potentially large network of coordinated stationary and mobile platforms carrying sensors of diverse modalities. The promise of IIS lies in their ability to continuously and robustly optimize their performance by intelligently exploiting massive amounts of sensor data in addition to their ability to effectively navigate and coordinate their sensing and computational assets.To date, the core issues underlying IIS have been studied largely in isolation in different communities. It is our belief that real progress on IIS requires a coordinated effort based on a unified mathematical and algorithmic foundation that supports not only efficient sensing, processing, data fusion, and decision making, but also direct performance analysis and prediction. This Marie Curie project will develop a principled theory of IIS that provides predictable, optimal performance for a range of different IIS problems through the effective utilization of the available network of resources. The mathematical foundation of our approach represents a profound re-thinking of the sensor data models and representations based on sparsity and combinatorial optimization algorithms based on submodularity. By unifying concepts from statistical signal processing, geometrical modeling and combinatorial optimization, we develop novel theories and rigorous algorithms towards the fundamental intellectual problem of automated scientific discovery. We will apply and evaluate our approaches on natural image understanding and environmental monitoring to provide a broad scaffold for framing numerous signal processing and machine learning problems encountered in diverse data modalities.

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