EE Seminar: Spectral methods for unsupervised ensemble learning and latent variable models
(The talk will be given in English)
Speaker: Dr. Ariel Jaffe
Weizmann Institute of Science
Monday, April 9th, 2018
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering
Spectral methods for unsupervised ensemble learning and latent variable models
Abstract
With the availability of huge amounts of unlabeled data, unsupervised learning methods are gaining increasing popularity and importance. We focus on ”unsupervised ensemble learning”, where one obtains the predictions of multiple classifiers over a set of unlabeled instances.
The classifiers may be human experts as in crowdsourcing, or prediction algorithms developed by research groups worldwide. The challenge is to estimate the accuracies of the different classifiers and combine them to an accurate meta-learner.
To tackle this problem, we show how it relates to latent variable models, and derive simple estimates for the classifiers’ accuracies based on a spectral analysis of the observed data. On the experimental side, we apply our methods to a problem in Computational Biology, where for various classification tasks one combines the results of multiple algorithms for improved accuracy.
In the second part of the talk, I will focus on extending the techniques developed for unsupervised ensemble learning to a specific family of linear latent variable models.
For cases where the latent layer is binary, we derive an interesting relation between the model parameters and the relatively recent notion of tensor eigenvectors of the data higher order moments.
We apply our methods to the problem of inferring global ancestry in population genetics.
Short bio
Ariel Jaffe is currently a PhD student at the faculty of Applied Mathematics, the Weizmann institute of Science. His main research interests include Statistical Machine Learning and Signal Processing.
Prior and during his PhD studies, he led the research and development of the Duchifat project (2010-2017), where two Nano-satellites were developed and operated by teams of high school students. In 2014 he was chosen as an Israeli representative to the UN Outer Space Affairs.
Between 2011-2013 he was with the CTO team in Alvarion, where he specialized in algorithms for indoor localization.
From August, he is scheduled to begin a position as a Gibbs assistant professor at the Yale University Applied Math department.
