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SPECGEO SIGNED

Spectral geometric methods in practice

Total Cost €

0

EC-Contrib. €

0

Partnership

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 SPECGEO project word cloud

Explore the words cloud of the SPECGEO project. It provides you a very rough idea of what is the project "SPECGEO" about.

ranging    removal    small    data    geometry    largely    abstract    perturbation    geometric    picture    theory    science    contradicts    analogous    pervasive    domains    crude    mainly    limited    techniques    point    transformations    bounds    computer    valuable    framework    infeasible    learning    contending    dimensional    incompleteness    interpreted    corrupted    machine    apparent    view    epsilon    kinds    network    undergoing    induce    inconsistency    little    arbitrary    biology    modality    lack    decomposition    toward    linear    directed    analytical    operator    operators    missing    fourier    behavior    models    surfaces    employed    efforts    adoption    uses    theoretical    despite    fact    deal    acceptance    constructed    cross    instability    world    vision    spectral    graphs    computational    settings    primarily    fundamentally    eigendecomposition    branches    suboptimal    single    tools    devoted    motivated    corruption    outstanding    presumption    lies   

Project "SPECGEO" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA 

Organization address
address: Piazzale Aldo Moro 5
city: ROMA
postcode: 185
website: www.uniroma1.it

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Total cost 1˙434˙000 €
 EC max contribution 1˙434˙000 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2018-STG
 Funding Scheme ERC-STG
 Starting year 2018
 Duration (year-month-day) from 2018-09-01   to  2023-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA IT (ROMA) coordinator 1˙434˙000.00

Map

 Project objective

Spectral geometry concerns the study of the geometric properties of data domains, such as surfaces or graphs, via the spectral decomposition of linear operators defined upon them. Due to their valuable properties analogous to Fourier theory, such methods find widespread use in several branches of computer science, ranging from computer vision to machine learning and network analysis.

Despite their pervasive presence, very little efforts have been devoted to the design and application of spectral techniques that deal with corrupted, missing, high-dimensional or abstract data undergoing complex transformations. This lack of focus is mainly motivated by the widespread acceptance, supported in part by theoretical results, that an ε-perturbation to the geometry of the data (as small as the removal of a single point) can induce arbitrary changes in the operator’s eigendecomposition – leading to a limited adoption of spectral models in real-world applications. This project challenges this view, contending that such presumption of instability is primarily due to a suboptimal choice of the analytical tools that are currently being employed, and which only provide part of the picture. In fact, strong evidence largely contradicts the expected behavior on real geometric data. The reason behind this apparent inconsistency lies in the different focus of current methods, which provide crude bounds and are directed toward other kinds of perturbation than those observed in real settings.

The ambitious goal of this project is to develop a novel theoretical and computational framework that will fundamentally change the way spectral techniques are constructed, interpreted, and applied. These tools will enable a range of currently infeasible uses of spectral methods on real data. They will deal with strong incompleteness, corruption and cross-modality, and they will be applied to outstanding problems in geometry processing, computer vision, machine learning, and computational biology.

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The information about "SPECGEO" are provided by the European Opendata Portal: CORDIS opendata.

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