There are four challenges in Topic Modeling: (i) Scaling up to very large data sets of billions of tokens (ii) Learning models with 100K + topics and (iii) doing so with a (provable) polynomial time algorithm with good error bounds which also (iv) performs well empirically on real corpora. We demonstrate all of the above starting with a new model.

Joint work with : Chiranjib Bhattacharyya and Harsha Simhadri