This Sunday, I will be out of town for ICDM conference held in Miami, FL.
I will present my paper:
Uncovering Groups via Heterogeneous Interaction Analysis.
This work addresses the community detection problem when multiple different types of interactions are presented between the same set of users.
A more general case is that users registered at different social media sites. Can we somehow uncover the hidden community structure?
We show that using an integration based on structural features is more robust. For evaluation, I proposed a simple cross-dimension network validation scheme. Similar to cross validation. This could be used as a simple rule for evaluation in the future.
Of course, there are many interesting directions to pursue in the future. One important aspect is that some of the dimensions are noisy. Is it possible to identify them? Is this the same as tensor decomposition?
"Our Days Are Numbered"
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[image: Proofs are amenable to chess techniques. "Our Days are Numbered".]
Slide in Lev Reyzin's JMM talk "Problems in AI and ML for Mathematicians"
Reyz...
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