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EMNLP'21: When differential privacy meets NLP
TUTORIAL: Recent Development in Differential Privacy I
Differentially Private Estimation via Statistical Depth
Differentially Private Sampling from Distributions
Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained...
Robust Statistics and Bias Correction: Ideas for Differential Privacy and Utility
From Robustness to Privacy and Back
STOC 2022 - Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exp Mech
Differentially Private Inference for Binomial Data
From Robustness to Privacy and Back
Certified Robustness to Adversarial Examples with Differential Privacy
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Last Updated: September 6, 2026
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Summary
Sewoong Oh (University of Washington, Seattle) ... Consider a scenario where we are training a model or performing CONFERENCE Recording during the thematic meeting : «Meeting in Mathematical Jörg Drechsler (Institute for Employment Research) simons.berkeley.edu/talks/tba-52 Slides and paper available at Github: github.com/habernal/emnlp2021- Aaron Roth, University of Pennsylvania Aaron Roth & Adam Smith ... Speaker: Ryan Cumings-Menon, US Census Bureau Date: July 26th, 2022 Part of the "Workshop on A Google TechTalk, presented by Marika Swanberg, 2023-08-22 Google Algorithms Seminar. ABSTRACT: We initiate an ... Katrina Ligett, Hebrew University of Jerusalem simons.berkeley.edu/talks/katrina-ligett-12-1-17 Optimization, Roberto Molinari (Pennsylvania State University) Lydia Zakynthinou (UC Berkeley) simons.berkeley.edu/talks/lydia-zakynthinou-uc-berkeley-2023-09-08 Efficient Mean Estimation with Pure Jordan Awan (Pennsylvania State University) Lydia Zakynthinou Ninth Annual Industry Day.
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