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Research Internship
In this project, we will look at the intersection of differential privacy and fairness of machine learning algorithms. To do this, we will exploit recent learning theoretic results showing equivalence of online and private learning. This internship is expected to be very theoretical with minimal coding.
The applicant is expected to be knowledgeable about learning theory and particularly online learning. This includes being able to read and understand papers on PAC learnability, generalisation of machine learning models, etc.
It is also helpful but not strictly required to be knowledgable about differential privacy.
Keywords: Privacy, Fairness, Online Learning
To apply for the position, please write a brief paragraph about your experience in online learning and learning theory. As attachments to the application, please send in your CV and your transcripts.
To apply for the position, please write a brief paragraph about your experience in online learning and learning theory. As attachments to the application, please send in your CV and your transcripts.
The goal is to arrive at a publication in the above mentioned topic.
The goal is to arrive at a publication in the above mentioned topic.