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,...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Understanding the data structures in a program is crucial to understanding how the program works, or why it doesn't work. Inspecting the code that implements the data structu...
Edward Aftandilian, Sean Kelley, Connor Gramazio, ...
—One of the key challenges in modern real-time embedded systems is safe composition of different software components. Formal verification techniques provide the means for design...
Background: For many types of analyses, data about gene structure and locations of non-coding regions of genes are required. Although a vast amount of genomic sequence data is ava...
Oliver Keller, Florian Odronitz, Mario Stanke, Mar...