Výsledky vyhľadávania - Single logical and abstracts algorithm, data and program scheme

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    Learning any memory-less discrete semantics for dynamical systems represented by logic programs Autor Ribeiro, Tony, Folschette, Maxime, Magnin, Morgan, Inoue, Katsumi

    ISSN: 0885-6125, 1573-0565
    Vydavateľské údaje: New York Springer US 01.10.2022
    Vydané v Machine learning (01.10.2022)
    “… However, other dynamics exist in the field of logical modeling, in particular the asynchronous semantics which is widely used to model biological systems…”
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    Survivable lightpath routing: a new approach to the design of WDM-based networks Autor Modiano, E., Narula-Tam, A.

    ISSN: 0733-8716, 1558-0008
    Vydavateľské údaje: New York IEEE 01.05.2002
    “… We call such a routing survivable and develop algorithms for survivable routing of a logical topology…”
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  4. 4

    A dynamic voting scheme in distributed systems Autor Davcev, D.

    ISSN: 0098-5589, 1939-3520
    Vydavateľské údaje: New York IEEE 01.01.1989
    “…A dynamic weighted voting scheme for consistency and recovery control of replicated files in distributed systems is presented…”
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    Cooperative and competitive concurrency in scientific computing. A full open-source upgrade of the program for dynamical calculations of RHEED intensity oscillations Autor Daniluk, Andrzej

    ISSN: 0010-4655, 1879-2944, 1386-9485
    Vydavateľské údaje: Elsevier B.V 01.06.2011
    Vydané v Computer physics communications (01.06.2011)
    “…A computational model is a computer program, which attempts to simulate an abstract model of a particular system…”
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    A Design of Autonomous Error-Tolerant Architectures for Massively Parallel Computing Autor Liu, Lizheng, Jin, Yi, Liu, Yi, Ma, Ning, Huan, Yuxiang, Zou, Zhuo, Zheng, Lirong

    ISSN: 1063-8210, 1557-9999, 1557-9999
    Vydavateľské údaje: New York IEEE 01.10.2018
    “… A nearby error sensing mechanism is designed to discover faults, and an active evolution scheme is studied to handle unrecoverable errors…”
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    A Study of Two Sampling Methods for Analyzing Large Datasets with ILP Autor Srinivasan, Ashwin

    ISSN: 1384-5810, 1573-756X
    Vydavateľské údaje: New York Springer Nature B.V 01.03.1999
    Vydané v Data mining and knowledge discovery (01.03.1999)
    “… We examine two schemes that allow an ILP system to construct theories by sampling from this large pool of data…”
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