This paper presents a framework for a learning based approach to dynamically evolve the conceptual structure of a database in order to facilitate virtual representation of data in ...
Abstract. Statistical debugging uses machine learning to model program failures and help identify root causes of bugs. We approach this task using a novel Delta-Latent-Dirichlet-Al...
David Andrzejewski, Anne Mulhern, Ben Liblit, Xiao...
This work presents a study to bridge topic modeling and personalized search. A probabilistic topic model is used to extract topics from user search history. These topics can be se...
The latent topic model plays an important role in the unsupervised learning from a corpus, which provides a probabilistic interpretation of the corpus in terms of the latent topic...
This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discreteevent systems; entities, resour...