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Relational Learning with Polynomials

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00197044" target="_blank" >RIV/68407700:21230/12:00197044 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Relational Learning with Polynomials

  • Original language description

    We describe a conceptually simple framework for transformation-based learning in hybrid relational domains. The proposed approach is related to hybrid Markov logic and to Gaussian logic framework. We evaluate the approach in three domains and show that it can achieve state-of-the-art performance while using only limited amount of information.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GAP103%2F11%2F2170" target="_blank" >GAP103/11/2170: Transferring ILP techniques to statistical relational learning</a><br>

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2012

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of IEEE 24th International Conference on Tools with Artificial Intelligence

  • ISBN

    978-0-7695-4915-6

  • ISSN

    1082-3409

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    1145-1150

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Los Alamitos

  • Event location

    Athens

  • Event date

    Nov 7, 2012

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article