Sparse Topic Modeling: Computational Efficiency, Near-Optimal Algorithms, and Statistical Inference
Description
Sparse topic modeling under the probabilistic latent semantic indexing (pLSI) model is studied. Novel and computationally fast algorithms for estimation and inference of both the word-topic matrix and the topic-document matrix are proposed and their
