High-Dimensional Statistics

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Bounding Training Data Reconstruction in Private (Deep) Learning (2022, methodology): “To extend it to general order α , one promising direction is to use minimax bounds (Rigollet & H¨utter, 2015) to establish a relationship between parameter estimation and hypothesis testing, which enables the use of general DP accountants to derive MSE lower bounds for DRAs.”
High‐dimensional macroeconomic forecasting and variable selection via penalized regression (2019, methodology): “(a) Since Xi is subG(α 2 i ), we obtain E|X|k ≤ (2α2i )k/2kΓ(k/2); see Rigollet and Hütter (2017), for instance.”
Adversarially Robust Generalization Requires More Data (2018, methodology): “7 from Rigollet and Hütter [43] for the weighted combination of independent sub-gaussian random variables, we get that”