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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Kumar, S; others,

Center of excellence for mobile sensor Data-to-Knowledge (MD2K) Journal Article

In: Journal of the American Medical Informatics Association, 22 , pp. 1137–1142, 2015, (<p>n/a</p>).

Abstract | Links | BibTeX

Mayberry, Addison; Hu, Pan; Tun, Yamin; Smith-Freedman, Duncan; Ganesan, Deepak; Salthouse, Christopher; Marlin, Benjamin M

CIDER: Enabling Robustness-Power Tradeoffs on a Computational Eyeglass Conference

Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, ACM ACM, 2015, (<p>n/a</p>).

Abstract | BibTeX

Li, Steven Cheng-Xian; Marlin, Benjamin

Classification of Sparse and Irregularly Sampled Time Series with Mixtures of Expected Gaussian Kernels and Random Features Journal Article

In: Proceedings of the 31st Conference on Uncertainty in Artficial Intelligence(UAI-15), 2015, (<p>n/a</p>).

Abstract | BibTeX

Winner, Kevin; Bernstein, Garrett; Sheldon, Dan

Inference in a Partially Observed Queuing Model with Applications in Ecology Conference

Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015, (<p>n/a</p>).

Abstract | BibTeX

Iyengar, Srinivasan; Kalra, Sandeep; Ghosh, Anushree; Irwin, David; Shenoy, Prashant; Marlin, Benjamin

iProgram: Inferring Smart Schedules for Dumb Thermostats Conference

Proceedings of the 2Nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments, BuildSys textquoteright15 ACM ACM, New York, NY, USA, 2015, ISBN: 978-1-4503-3981-0, (<p>n/a</p>).

Abstract | Links | BibTeX

38 entries « 4 of 8 »