Tudor Cebere
@tcebere.bsky.social
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PhD student in differential privacy & learning at Inria 🇫🇷
reposted by
Tudor Cebere
Differential Privacy Papers
7 months ago
Beyond Laplace and Gaussian: Exploring the Generalized Gaussian Mechanism for Private Machine Learning Roy Rinberg, Ilia Shumailov, Vikrant Singhal, Rachel Cummings, Nicolas Papernot
http://arxiv.org/abs/2506.12553
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Excited to be in Singapore for ICLR, presenting our work on privacy auditing (w/ Aurélien &
@nicolaspapernot.bsky.social
). If you are interested in differential privacy/privacy auditing/security for ML, drop by (#497 26 Apr 10-12:30 pm) or let's grab a coffee! ☕
openreview.net/forum?id=xzK...
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Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model
Machine learning models can be trained with formal privacy guarantees via differentially private optimizers such as DP-SGD. In this work, we focus on a threat model where the adversary has access...
https://openreview.net/forum?id=xzKFnsJIXL
9 months ago
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reposted by
Tudor Cebere
Jelani Nelson
about 1 year ago
Postdoc opportunity: if interested in a postdoc related to sketching starting Summer/Fall'25, especially applied to more efficient foundation model architectures (e.g. faster approx attention), please follow the instructions on the left column of
theory.cs.berkeley.edu/postdoc.html
by Jan 31
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