Result for 803CE2DD019B4E70EF3CEE86AE77C96873EFA027

Query result

Key Value
FileName./usr/lib64/R/library/ELMSO/help/ELMSO.rdx
FileSize226
MD5C52402D72F6AEDEC72F3BAF5F3CB2F24
SHA-1803CE2DD019B4E70EF3CEE86AE77C96873EFA027
SHA-2560CF1C205EE9AD5E8D62E516E9D24BCB1FBFF428ABAC075B997E2886DAE54CEAB
SSDEEP6:XtVFofnFdjCQKEUwQgE2wwEz4aMO7Di48S:XenHjTLdElwEz4Q7DFp
TLSHT1F6D02339431867F2E77382781845367326F0B4015D61D9AD5CB6535F1D43065D8C105F
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