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Boston University, Boston, USA
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Willow's innovative type-and-effect system reveals hidden timing dependencies in reactive programs, enabling static detection of performance-degrading render cascades.
Knowing the attribute dependencies within a population lets attackers infer membership with surprising accuracy, even against statistical releases designed to protect privacy.
Oblivious differential privacy can achieve exponential accuracy under continual observation, while adaptive differential privacy provably fails after a constant number of releases, revealing a stark separation.
Adaptive data analyses can lead to high generalization errors, but a new program analysis framework offers a way to effectively manage these errors through structured representation and analysis.
