We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
— In this work, a probabilistic model is established for recurrent networks. The EM (expectation-maximization) algorithm is then applied to derive a new fast training algorithm f...
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
This paper analyzes and improves the linearized Bregman method for solving the basis pursuit and related sparse optimization problems. The analysis shows that the linearized Bregma...
Developing and analyzing schedules is essential for successfully controlling the time aspect of construction projects. The critical path method of scheduling is by far the most wi...