Result for 374BC1092739C447B3D005FADF255FD3AF822D3B

Query result

Key Value
FileName./usr/lib64/R/library/ELMSO/Meta/package.rds
FileSize1307
MD52318D6CFDDA95E750A31F4D468B6C6A3
SHA-1374BC1092739C447B3D005FADF255FD3AF822D3B
SHA-2568B5B4AEEE7198C0C2EAA6C32D88646A39FF097B7C51B056152A065A99A8BB62A
SSDEEP24:X3xE0yR0SO1wHXVo2+MtmaHHtzo5syIiKrVf6cEJJBp+dPAkrq++v2:X3xLSOu3ttXHtc5syfunCJB6AHv2
TLSHT195211D7707450822FCEC518D24580E30B02F4159DFD718DCFB4B9151966AD346C59357
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD568101C092A171C5B50AE5E4C669F4E14
PackageArchx86_64
PackageDescriptionAn implementation of the algorithm described in "Efficient Large- Scale Internet Media Selection Optimization for Online Display Advertising" by Paulson, Luo, and James (Journal of Marketing Research 2018; see URL below for journal text/citation and <http://faculty.marshall.usc.edu/gareth-james/Research/ELMSO.pdf> for a full-text version of the paper). The algorithm here is designed to allocate budget across a set of online advertising opportunities using a coordinate-descent approach, but it can be used in any resource-allocation problem with a matrix of visitation (in the case of the paper, website page- views) and channels (in the paper, websites). The package contains allocation functions both in the presence of bidding, when allocation is dependent on channel-specific cost curves, and when advertising costs are fixed at each channel.
PackageNameR-ELMSO
PackageReleaselp153.2.3
PackageVersion1.0.1
SHA-14B93F4F038D9BC32E02F6C87BBD38B17618F6B3E
SHA-2561416D2426189C114C288DED6F733F7FE4DEECD638F3275686224D91B746F4943