@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

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    dct:description "The notable changes over the current version: - worked example of convergence rates showing SAG can be faster than first-order methods - pointing out that the storage cost is O(n) for linear models - the more-stable line-search - comparison to additional optimal SG methods - comparison to rates of coordinate descent methods in quadratic case." ;
    dct:identifier "hal-00674995" ;
    dct:issued "2026-05-13T02:48:19.990276"^^xsd:dateTime ;
    dct:language "en" ;
    dct:modified "2026-05-13T02:48:19.990281"^^xsd:dateTime ;
    dct:publisher <https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> ;
    dct:title "A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets" ;
    dcat:contactPoint [ a vcard:Organization ;
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        "mathmath-ocmathematics-mathoptimization-and-control-mathoc",
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    dcat:landingPage <NIPS%2712%20-%2026%20th%20Annual%20Conference%20on%20Neural%20Information%20Processing%20Systems%20%282012%29> .

<NIPS%2712%20-%2026%20th%20Annual%20Conference%20on%20Neural%20Information%20Processing%20Systems%20%282012%29> a foaf:Document .

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    dct:title "A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets" ;
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