Quan Zhou

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20232025

most citedOptimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics

1 citations · 1 across the 7 of their papers we have counts for

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stat.CO2025

Uniform ergodicity and spectral gap of importance-tempered MCMC with heavy-tailed targets

Quan Zhou

We study the importance-tempered random-walk Metropolis (RWM) algorithm on $R^{d}$ , which targets the tempered density $π_{β} (x) \propto π (x)^{β}$ with $β \in (0, 1)$ and corrects…

stat.CO2023

Importance is Important: Generalized Markov Chain Importance Sampling Methods

Guanxun Li, Aaron Smith, Quan Zhou

We show that for any multiple-try Metropolis algorithm, one can always accept the proposal and evaluate the importance weight that is needed to correct for the bias without extra c…