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.

Publications

38 entries « 3 of 8 »

2016

Dadkhahi, Hamid; Saleheen, Nazir; Kumar, Santosh; Marlin, Benjamin

Learning Shallow Detection Cascades for Wearable Sensor-Based Mobile Health Applications Conference

ICML On Device Intelligence Workshop, 2016, (<p>n/a</p>).

Abstract | BibTeX

Nguyen, Thai; Adams, Roy J; Natarajan, Annamalai; Marlin, Benjamin M

Parsing Wireless Electrocardiogram Signals with the CRF-CFG Model Proceeding

2016, (<p>n/a</p>).

Abstract | BibTeX

Winner, Kevin; Sheldon, Daniel

Probabilistic Inference with Generating Functions for Poisson Latent Variable Models Proceeding

Barcelona, Spain, 2016.

BibTeX

2015

Adams, Roy; Thomaz, Edison; Marlin, Benjamin M

Hierarchical Nested CRFs for Segmentation and Labeling of Physiological Time Series Conference

NIPS Workshop: Machine Learning for Healthcare, 2015.

BibTeX

Schein, Aaron; Paisley, John; Blei, David M; Wallach, Hanna

Bayesian poisson tensor factorization for inferring multilateral relations from sparse dyadic event counts Conference

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM ACM, 2015, (<p>n/a</p>).

Abstract | BibTeX

38 entries « 3 of 8 »