We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
This paper introduces an information theoretic approach to verification of modular causal probabilistic models. We assume systems which are gradually extended by adding new functi...
—In this paper, we propose P3 -coupon, a Prompt and Privacy-preserving electronic coupon distribution system based on a Probabilistic one-ownership forwarding algorithm. In this ...
Boying Zhang, Jin Teng, Xiaole Bai, Zhimin Yang, D...
The advent of social tagging systems has enabled a new community-based view of the Web in which objects like images, videos, and Web pages are annotated by thousands of users. Und...
Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. However, word order and phrases are often critical to capturing the meaning of text in...