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BLACKJACK SIGNED

Fast Monte Carlo integration with repulsive processes

Total Cost €

0

EC-Contrib. €

0

Partnership

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 BLACKJACK project word cloud

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

colliding    galaxies    convergence    meanwhile    monte    computer    experimental    tool    tools    takes    quadrature    schemes    cheap    explicitly    mathematical    carlo    communication    parallelization    ubiquitous    first    parallel    fitting    hammer    scientific    ecosystems    introduce    statistical    biology    qualitatively    computationally    variance    estimation    point    repulsiveness    electrons    dynamics    single    turn    prototypal    expensive    algorithm    simulations    determinantal    data    routine    statisticians    blackjack    hardware    serial    fast    signal    poorly    computing    proved    rate    hours    astrophysicists    minutes    running    filling    nodes    algorithms    efficient    independent    processers    computational    evaluation    models    millions    inference    box    sciences    evaluations    volumes    chain    physics    architectures    instance    biologists    particle    intricate    learners    world    limited    evolution    markov    ecologists    slow    unlock    model    machine    repulsive    cells    copies   

Project "BLACKJACK" data sheet

The following table provides information about the project.

Coordinator
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS 

Organization address
address: RUE MICHEL ANGE 3
city: PARIS
postcode: 75794
website: www.cnrs.fr

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 France [FR]
 Total cost 1˙489˙000 €
 EC max contribution 1˙489˙000 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2019-STG
 Funding Scheme ERC-STG
 Starting year 2020
 Duration (year-month-day) from 2020-02-01   to  2025-01-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS FR (PARIS) coordinator 1˙489˙000.00

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 Project objective

Expensive computer simulations have become routine in the experimental sciences. Astrophysicists design complex models of the evolution of galaxies, biologists develop intricate models of cells, ecologists model the dynamics of ecosystems at a world scale. A single evaluation of such complex models takes minutes or hours on today's hardware. On the other hand, fitting these models to data can require millions of serial evaluations. Monte Carlo methods, for example, are ubiquitous in statistical inference for scientific data, but they scale poorly with the number of model evaluations. Meanwhile, the use of parallel computing architectures for Monte Carlo is often limited to running independent copies of the same algorithm. Blackjack will provide Monte Carlo methods that unlock inference for expensive models in biology by directly addressing the slow rate of convergence and the parallelization of Monte Carlo methods.

The key to take down the Monte Carlo rate is to introduce repulsiveness between the quadrature nodes. For instance, we recently proved that determinantal point processes, a prototypal repulsive distribution introduced in physics, improve the Monte Carlo convergence rate, just like electrons lead to low-variance estimation of volumes by efficiently filling a box. Such results lead to open computational and statistical challenges. We propose to solve these challenges, and make repulsive processes a novel tool for applied statisticians, signal processers, and machine learners.

Still with repulsiveness as a hammer, we will design the first parallel Markov chain Monte Carlo algorithms that are qualitatively different from running independent copies of known algorithms, i.e., that explicitly improve the order of convergence of the single-machine algorithm. To this end, we will turn mathematical tools such as repulsive particle systems and non-colliding processes into computationally cheap, communication-efficient Monte Carlo schemes with fast convergence.

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

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