Newtonian Monte Carlo: single-site MCMC meets second-order gradient methods

2 code implementations • 15 Jan 2020 • Nimar S. Arora, Nazanin Khosravani Tehrani, Kinjal Divesh Shah, Michael Tingley, Yucen Lily Li, Narjes Torabi, David Noursi, Sepehr Akhavan Masouleh, Eric Lippert, Erik Meijer

NMC is similar to the Newton-Raphson update in optimization where the second order gradient is used to automatically scale the step size in each dimension.

Second-order methods Variational Inference

Uncertainty Estimation For Community Standards Violation In Online Social Networks

no code implementations • 30 Sep 2020 • Narjes Torabi, Nimar S. Arora, Emma Yu, Kinjal Shah, Wenshun Liu, Michael Tingley

This task is exceedingly hard because even though we can easily get the ML scores or features for all of the billions of items we can only get ground truth labels on a few thousands of these items due to practical considerations.

Newtonian Monte Carlo: a second-order gradient method for speeding up MCMC

no code implementations • pproximateinference AABI Symposium 2019 • Nimar S. Arora, Nazanin Khosravani Tehrani, Kinjal Divesh Shah, Michael Tingley, Yucen Lily Li, Narjes Torabi, David Noursi, Sepehr Akhavan Masouleh, Eric Lippert, Erik Meijer

NMC is similar to the Newton-Raphson update in optimization where the second order gradient is used to automatically scale the step size in each dimension.

Variational Inference