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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Huang, Haibin; Kalogerakis, Evangelos; Marlin, Benjamin

Analysis and synthesis of 3D shape families via deep-learned generative models of surfaces Conference

Symposium on Geometry Processing, 2015, (<p>n/a</p>).

Abstract | Links | BibTeX


Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

Conditional Random Fields for Morphological Analysis of Wireless ECG Signals Conference

5th Annual conference on Bioinformatics, Computational Biology and Health Informatics, Newport Beach, CA, 2014.

Abstract | BibTeX

Mayberry, Addison; Hu, Pan; Marlin, Benjamin; Ganesan, Deepak; Salthouse, Christopher

iShadow: Design of a Wearable, Real-Time Mobile Gaze Tracker Conference

12th International Conference on Mobile Systems, Applications, and Services, 2014.

Abstract | BibTeX

Adams, Roy J; Sadasivam, Rajani S; Balakrishnan, Kavitha; Kinney, Rebecca L; Houston, Thomas K; Marlin, Benjamin M

PERSPeCT: Collaborative Filtering for Tailored Health Communications Conference

Proceedings of the 8th ACM Conference on Recommender Systems, RecSys textquoteright14 ACM ACM, 2014, ISBN: 978-1-4503-2668-1, (<p>n/a</p>).

Abstract | Links | BibTeX

Learned-Miller, Erik; Marlin, Benjamin M; Kae, Andrew

The Shape-Time Random Field for Semantic Video Labeling Proceeding

2014, (<p>n/a</p>).

Abstract | Links | BibTeX

38 entries « 6 of 8 »