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Interaction-Partitioned Topic Models (IPTM) using a Point Process Approach
I have spent very long time figuring out the possible bugs, but failed.
I was able to re-derive exactly the same sampling equation as cluster LDA, so I do not see any mathematical error.
IP assignments and topic assignments from backward sampling always has larger variance than those from forward sampling, and the difference gets larger as we run more outer iterations.
To test this in the simplest setting of cluster LDA (no other variables other than cd and z), I ran 'clusterLDA.R' code in GiR2 folder and I get the same odd results. Is there anything I am totally missing?
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