About the Lab

The MLDS lab focused on the development of machine learning models and algorithms for addressing a variety of challenging problems in the areas of computational social science, computational ecology, computational behavioral science and computational medicine.

The MLDS lab’s research continues in multiple labs within the the College of Information and Computer Sciences including the REML lab, the SLANG lab, and Prof. Sheldon’s research group.


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Xue, S; Fern, A; Sheldon, D

Scheduling Conservation Designs via Network Cascade Optimization Conference

Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012, (<p>n/a</p>).

Abstract | BibTeX

Krafft, Peter; Moore, Juston; Wallach, Hanna; Desmarais, Bruce

Topic-Partitioned Multinetwork Embeddings Conference

Advances in Neural Information Processing Systems Twenty-Five, Lake Tahoe, NV, 2012.

Abstract | BibTeX

Marlin, Benjamin M; Kale, David C; Khemani, Robinder G; Wetzel, Randall C

Unsupervised pattern discovery in electronic health care data using probabilistic clustering models Conference

Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, IHI textquoteright12 ACM ACM, New York, NY, USA, 2012, ISBN: 978-1-4503-0781-9.

Abstract | Links | BibTeX

38 entries « 8 of 8 »