Topic models are a useful tool for analyzing large text collections, but have previously been applied in only monolingual, or at most bilingual, contexts. Meanwhile, massive colle...
David M. Mimno, Hanna M. Wallach, Jason Naradowsky...
We consider the use of Bayesian topic models in the analysis of computer network traffic. Our approach utilizes latent Dirichlet allocation and time-varying dynamic latent Dirich...
This paper focuses on a solution to better adapt ASR systems, whose language models (LM) are usually trained on topic-independent corpora, to new topics, in particular in the case...
By its very nature DSP is a mathematically heavy topic and to fully understand it students need to understand the mathematical developments underlying DSP topics. However, relying...
Abstract. In this paper, we present a new approach to indexing multidimensional data that is particularly suitable for the efficient incremental processing of nearest neighbor quer...