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Efficiently Sampling Multiplicative Attribute Graphs Using a Ball-Dropping Process

Friday, April 20, 11AM – 12PM
ACE 6.304

S V N Vishwanathan

In this talk I will describe the first sub-quadratic sampling algorithm for the Multiplicative Attribute Graph Model (MAGM, Kim and Leskovec 2010). To design our algorithm, we first define a stochastic ball-dropping process(BDP). Although a special case of this process was introduced as an efficient approximate sampling algorithm for the Kronecker Product Graph Model (KPGM, Leskovec et al 2010), neither why such an approximation works nor what is the actual distribution this process is sampling from has been addressed so far to the best of our knowledge.

Our rigorous treatment of the BDP enables us to clarify the rational behind a BDP approximation of KPGM, and design an efficient sampling algorithm for the MAGM.

Joint work with Hyokun Yun.

Hosted by Inderjit Dhillon