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Jonathan Ullman

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Virtual talk by Jonathan Ullman (Northeastern)Trust in Decentralized Systems 20262026-03-16
Shows that for a noisy Gaussian mean setting membership inference can be information-theoretically possible yet demand an auxiliary sample size Omega(d) that…
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Program Analysis for Adaptive Data AnalysisPLDI 20242024-06-24
Static analysis estimates the adaptivity of while-like adaptive data analyses by building a weighted dependency graph whose node weights are reachability upper…
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Differential Privacy And The Complexity Of Simple QueriesRigorous Evidence for Information-Computation Trade-offs2021-09-13
Shows an explicit information–computation gap: answering k arbitrary bounded mean queries privately needs about √k samples with any polynomial-time algorithm…
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Algorithmic Stability for Interactive Data AnalysisOptimization, Statistics and Uncertainty2017-11-28
Interactive reuse of data causes severe overfitting: naive empirical answers let an adaptive procedure reach correlation about √D/√N (even perfect when D > N)…
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