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.
Approximate Inference in Collective Graphical Models Conference
In Proceedings of the 30th International Conference on Machine Learning (ICML), 2013., 2013.
Detecting Cocaine Use with Wearable Electrocardiogram Sensors Proceeding
Zurich, Switzerland, 2013.
Towards Collaborative Filtering Recommender Systems for Tailored Health Communications Proceeding
Washington D.C., 2013.
Collective Graphical Models Conference
Advances in Neural Information Processing Systems (NIPS 2011), 2012, (<p>n/a</p>).
Data Intensive Science Applied to Broad-Scale Citizen Science Booklet