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Model complexity of neural, radial, and kernel networks

Project goals

The project will contribute to development of theoretical foundations of neurocomputing. The goal of the research is to obtain new knowledge in terms of mathematical results describing capabilities and limitations of multilayer networks. Relationships between networks with various types of computational units (perceptrons, radial, and kernel), various parameters of these units will be described. Estimates of model complexities of networks will be derived in dependence on input dimensions, types of units and network architectures. Properties of high-dimensional tasks which can be represented or approximated by networks of reasonable sizes will be characterized. Optimal solutions of learning tasks from point of view of generalization and model complexity will be analyzed.

Keywords

multilayer networksperceptrons, radial and kernel computational unitsmodel complexityapproximation and representation of multivariable functions by neural networks

Public support

  • Provider

    Czech Science Foundation

  • Programme

    Standard projects

  • Call for proposals

    Standardní projekty 19 (SGA0201500001)

  • Main participants

    Ústav informatiky AV ČR, v. v. i.

  • Contest type

    VS - Public tender

  • Contract ID

    15-18108S

Alternative language

  • Project name in Czech

    Modelová složitost neuronových, radiálních a jádrových sítí

  • Annotation in Czech

    Projekt přispěje k budování teoretických základů neuropočítání. Cílem výzkumu je získat nové znalosti ve formě matematických výsledků popisujících schopnosti a omezení vícevrstvých sítí. Budou popsány vztahy mezi sítěmi s různými typy jednotek (perceptrony, radiálními a jádrovými) a různými parametry těchto jednotek. Budou odvozeny odhady modelové složitosti sítí v závislosti na vstupních dimenzích, počtech a typech jednotek a architekturách sítí. Budou charakterizovány vlastnosti vysoce dimenzionálních úloh, které lze reprezentovat nebo aproximovat sítěmi s přijatelnou složitostí. Budou analyzována optimální řešení úloh učení z hlediska generalizace a modelové složitosti.

Scientific branches

  • R&D category

    ZV - Basic research

  • CEP classification - main branch

    IN - Informatics

  • CEP - secondary branch

  • CEP - another secondary branch

  • 10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Completed project evaluation

  • Provider evaluation

    U - Uspěl podle zadání (s publikovanými či patentovanými výsledky atd.)

  • Project results evaluation

    The project deepened knowledge of the ability and limitation of multilayer neural networks, especially by estimating their complexity requirements wrt architectural design and other parameters. The evaluation of the PI is adequate, the project contributes mainly to the field of informatics and has the research output. Deficiencies in adherence to grant rules or funding have not occurred.

Solution timeline

  • Realization period - beginning

    Jan 1, 2015

  • Realization period - end

    Dec 31, 2017

  • Project status

    U - Finished project

  • Latest support payment

    Apr 5, 2017

Data delivery to CEP

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

  • Data delivery code

    CEP18-GA0-GA-U/02:1

  • Data delivery date

    May 4, 2018

Finance

  • Total approved costs

    3,400 thou. CZK

  • Public financial support

    3,400 thou. CZK

  • Other public sources

    0 thou. CZK

  • Non public and foreign sources

    0 thou. CZK

Basic information

Recognised costs

3 400 CZK thou.

Public support

3 400 CZK thou.

100%


Provider

Czech Science Foundation

CEP

IN - Informatics

Solution period

01. 01. 2015 - 31. 12. 2017