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Ilias Diakonikolas

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titleconferencedate
Non-Gaussian Component Analysis: Statistical Query Hardness and its ApplicationsRigorous Evidence for Information-Computation Trade-offs2021-09-13
Proves an SQ hardness theorem for Non‑Gaussian Component Analysis: if a univariate A matches the first m moments with N(0,1) and has finite chi-square…
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Computational-Statistical Tradeoffs in Robust High-Dimensional EstimationRobust and High-Dimensional Statistics (Simons Institute workshop, 2018)2018-10-29
Shows that beating the current epsilon·sqrt(log(1/epsilon)) error for robust high‑dimensional Gaussian mean estimation forces either statistical query model…
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Algorithmic High Dimensional Robust Statistics IFoundations of Data Science Boot Camp 20182018-08-27
Goal: recover a Gaussian mean in d dimensions with an epsilon fraction of corruptions and identity covariance. Transcript claims sample complexity…
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Algorithmic High Dimensional Robust Statistics IIFoundations of Data Science Boot Camp 20182018-08-27
Proves a concrete certificate: if the empirical covariance spectral norm stays within 1+δ then the empirical mean is robust under strong contamination, with…
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Learning and Testing Structured DistributionsInformation Theory, Learning and Big Data (Simons Institute, 2015)2015-03-16
Ilias Diakonikolas, University of Edinburgh Information Theory, Learning and Big Data http://simons.berkeley.edu/talks/ilias-diakonikolas-2015-03-19
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