I work in the machine learning group on several topics:
- Using technology to help in behavioral changes
- Measuring gait and balance (see the workshop on this subject here)
- Machine learning theory
- Machine learning debugging
- Fault detection
Bellow is a list of recent publications.
- Nathan Dowlin, Ran Gilad-Bachrach, Kim Laine, Kristin Lauter, Michael Naehrig, and John Wernsing, Manual for Using Homomorphic Encryption for Bioinformatics, no. MSR-TR-2015-87, 13 November 2015.
- Yoram Bachrach, Yehuda Finkelstein, Ran Gilad-Bachrach, Liran Katzir, Noam Koenigstein, Nir Nice, and Ulrich Paquet, Speeding Up the Xbox Recommender System Using a Euclidean Transformation for Inner-Product Spaces, October 2014.
- Alejandro Alanis, Trang Thai, Gerald Dejean, Ran Gilad-Bachrach, and Dimitrios Lymberopoulos, 3d Gesture recognition through RF sensing, no. MSR-TR-2014-81, June 2014.
- Erin Renshaw, Christopher J.C. Burges, and Ran Gilad-Bachrach, Selective Classifiers for Part-of-Speech Tagging, no. MSR-TR-2014-64, 16 May 2014.
- Pablo Paredes, Ran Gilad-Bachrach, Asta Roseway, Mary Czerwinski, and Kael Rowan, PopTherapy: Coping with Stress through Pop-Culture, IEEE Pervasive Health, May 2014.
- Pablo Paredes, Ran Gilad-Bachrach, Javier Hernandez, Mary Czerwinski, and Asta Roseway, PopTherapy: Coping with Stress through Pop-Culture, IEEE Pervasive Health 2014, May 2014.
- Pablo Paredes, Ran Gilad-Bachrach, Javier Hernandez, Mary Czerwinski, and Asta Roseway, PopTherapy: Coping with Stress through Pop-Culture, IEEE – Institute of Electrical and Electronics Engineers, May 2014.
- Jason D. Lee, Ran Gilad-Bachrach, and Rich Caruana, Using multiple samples to learn mixture models, in Neural Infromation Processing Systems (NIPS), Neural Information Processing Systems Foundation, December 2013.
- Jason D. Lee, Ran Gilad-Bachrach, and Rich Caruana, Using Multiple Samples to Learn Mixture Models - extended version, no. MSR-TR-2013-134, December 2013.
- Ran Gilad-Bachrach and Christopher J.C. Burges, Classifier Selection using the Predicate Depth , in Journal of Machine Learning Research (JMLR), December 2013.