no code implementations • NeurIPS 2015 • Siddhartha Banerjee, Peter Lofgren
We develop a new bidirectional algorithm for estimating Markov chain multi-step transition probabilities: given a Markov chain, we want to estimate the probability of hitting a given target state in $\ell$ steps after starting from a given source distribution.
1 code implementation • 21 Jul 2015 • Peter Lofgren, Siddhartha Banerjee, Ashish Goel
First, for the problem of estimating Personalized PageRank (PPR) from a source distribution to a target node, we present a new bidirectional estimator with simple yet strong guarantees on correctness and performance, and 3x to 8x speedup over existing estimators in experiments on a diverse set of networks.
