RaCT - Toward Amortized Ranking-Critical Training For Collaborative Filtering.

Sam Lobel; Chunyuan Li; Jianfeng Gao; Lawrence Carin

RaCT - Toward Amortized Ranking-Critical Training For Collaborative Filtering.

Sam Lobel, Chunyuan Li, Jianfeng Gao, Lawrence Carin

Research output: Contribution to conference › Paper › peer-review

Original language	English (US)
State	Published - 2020
Externally published	Yes

Bibliographical note

DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

Access to Document

https://dblp.org/rec/conf/iclr/LobelLGC20

Cite this

@conference{c8a5f3a7543f471bb044909a78342cf6,

title = "RaCT - Toward Amortized Ranking-Critical Training For Collaborative Filtering.",

author = "Sam Lobel and Chunyuan Li and Jianfeng Gao and Lawrence Carin",

note = "DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",

year = "2020",

language = "English (US)",

}

TY - CONF

T1 - RaCT - Toward Amortized Ranking-Critical Training For Collaborative Filtering.

AU - Lobel, Sam

AU - Li, Chunyuan

AU - Gao, Jianfeng

AU - Carin, Lawrence

N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2020

Y1 - 2020

M3 - Paper

ER -