Xiao-Li Meng | DeepAI

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∙ 10/19/2022

BELIEF in Dependence: Leveraging Atomic Linearity in Data Bits for Rethinking Generalized Linear Models

Two linearly uncorrelated binary variables must be also independent beca...

0 Benjamin Brown, et al. ∙

∙ 04/04/2022

Scalable Spike-and-Slab

Spike-and-slab priors are commonly used for Bayesian variable selection,...

3 Niloy Biswas, et al. ∙

∙ 06/10/2021

Are We There Yet? Big Data Significantly Overestimates COVID-19 Vaccination in the US

Public health efforts to control the COVID-19 pandemic rely on accurate ...

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∙ 10/17/2020

A Multi-resolution Theory for Approximating Infinite-p-Zero-n: Transitional Inference, Individualized Predictions, and a World Without Bias-Variance Trade-off

Transitional inference is an empiricism concept, rooted and practiced in...

0 Xinran Li, et al. ∙

∙ 08/28/2020

Double Happiness: Enhancing the Coupled Gains of L-lag Coupling via Control Variates

The recently proposed L-lag coupling for unbiased MCMC <cit.> calls for ...

0 Radu V. Craiu, et al. ∙

∙ 08/24/2020

Congenial Differential Privacy under Mandated Disclosure

Differentially private data releases are often required to satisfy a set...

0 Ruobin Gong, et al. ∙

∙ 06/16/2019

Designing Test Information and Test Information in Design

DeGroot (1962) developed a general framework for constructing Bayesian m...

0 David E. Jones, et al. ∙

∙ 12/24/2017

Judicious Judgment Meets Unsettling Updating: Dilation, Sure Loss, and Simpson's Paradox

Statistical learning using imprecise probabilities is gaining more atten...

0 Ruobin Gong, et al. ∙

∙ 11/26/2017

Calibration Concordance for Astronomical Instruments via Multiplicative Shrinkage

Calibration data are often obtained by observing several well-understood...

0 Yang Chen, et al. ∙

∙ 11/23/2017

Multiple Improvements of Multiple Imputation Likelihood Ratio Tests

Multiple imputation (MI) inference handles missing data by first properl...

0 Kin Wai Chan, et al. ∙

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