155 citations · 955 across the 56 of their papers we have counts for
3 papers · 1 filter
No Free Lunch for Stochastic Gradient Langevin Dynamics
Natesh S. Pillai, Aaron Smith, Azeem Zaman
As sample sizes grow, scalability has become a central concern in the development of Markov chain Monte Carlo (MCMC) methods. One general approach to this problem, exemplified by t…
Privacy-Preserving Race/Ethnicity Estimation for Algorithmic Bias Measurement in the U.S
Saikrishna Badrinarayanan, Osonde Osoba, Miao Cheng +4
AI fairness measurements, including tests for equal treatment, often take the form of disaggregated evaluations of AI systems. Such measurements are an important part of Responsibl…
Policy Gradients for Optimal Parallel Tempering MCMC
Daniel Zhao, Natesh S. Pillai
Parallel tempering is a meta-algorithm for Markov Chain Monte Carlo that uses multiple chains to sample from tempered versions of the target distribution, enhancing mixing in multi…