6 citations · 15 across the 6 of their papers we have counts for
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cs.LG2021
Information Theoretic Evaluation of Privacy-Leakage, Interpretability, and Transferability for Trustworthy AI
Mohit Kumar, Bernhard A. Moser, Lukas Fischer +1
In order to develop machine learning and deep learning models that take into account the guidelines and principles of trustworthy AI, a novel information theoretic trustworthy AI f…
cs.LG2021
Differentially Private Transferrable Deep Learning with Membership-Mappings
Mohit Kumar
This paper considers the problem of differentially private semi-supervised transfer and multi-task learning. The notion of \emph{membership-mapping} has been developed using measur…
cs.LG2021
Membership-Mappings for Data Representation Learning: Measure Theoretic Conceptualization
Mohit Kumar, Bernhard A. Moser, Lukas Fischer +1
A fuzzy theoretic analytical approach was recently introduced that leads to efficient and robust models while addressing automatically the typical issues associated to parametric d…