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Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax
  Rates, Covariate Quantization, and Uniform Recovery

Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery

30 December 2022
Junren Chen
Michael Kwok-Po Ng
Di Wang
    MQ
ArXivPDFHTML

Papers citing "Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery"

3 / 3 papers shown
Title
Quantized Low-Rank Multivariate Regression with Random Dithering
Quantized Low-Rank Multivariate Regression with Random Dithering
Junren Chen
Yueqi Wang
Michael Kwok-Po Ng
12
4
0
22 Feb 2023
Quantizing data for distributed learning
Quantizing data for distributed learning
Osama A. Hanna
Yahya H. Ezzeldin
Christina Fragouli
Suhas Diggavi
FedML
31
19
0
14 Dec 2020
A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust
  Low-Rank Matrix Recovery
A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust Low-Rank Matrix Recovery
Jianqing Fan
Weichen Wang
Ziwei Zhu
42
95
0
28 Mar 2016
1