Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Identification of the short DNA sequence motifs that serve as binding targets for transcription factors is an important challenge in bioinformatics. Unsupervised techniques from t...
Shaun Mahony, Panayiotis V. Benos, Terry J. Smith,...
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 ...
Spatio-temporal databases store information about the positions of individual objects over time. In many applications however, such as traffic supervision or mobile communication ...
Dimitris Papadias, Yufei Tao, Jun Zhang, Nikos Mam...
— In the past, there has been a tremendous advance in the area of simultaneous localization and mapping (SLAM). However, there are relatively few approaches for incorporating pri...
Michael Karg, Kai M. Wurm, Cyrill Stachniss, Klaus...