Result for 332F8206C358957E366A4E2DAEF63DFE9CD231B3

Query result

Key Value
FileName./usr/lib64/R/library/ELMSO/DESCRIPTION
FileSize1696
MD5C071FDF9A4D2CB00BB02D5819C9FC93A
SHA-1332F8206C358957E366A4E2DAEF63DFE9CD231B3
SHA-256453A74EA3CDFB70051F55580F3E1E32E83A3BBDBB252914CF9B7624586B7DA73
SSDEEP48:ztL612/1K2tnWTo22ZEYxRYthm047CMdSqkI0Nn1:p8C1LAo22KpqCMdS7I0r
TLSHT11A319627E5042373678911A334E613867334A157B6728A246D0DD9284F09F3EDBFBB5C
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
MD5D95A7A12DACF22B03D70E113354F50C1
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
PackageReleaselp153.2.1
PackageVersion1.0.1
SHA-1100BF97C0EB2DA6D3BF2A63A903E8B57497D1B98
SHA-256A7937B7163BB93D2C5AF95C968AD00587617C833806F8D953D3C7A741B4EE778