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.
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>).
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>).
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>).
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>).
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>).