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Stochastic Quasi-Newton Langevin Monte Carlo

ICML 2016 · Optimization › Optimizers · approach: Stochastic gradient MCMC · 32 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use dense L-BFGS inverse-Hessian approximations with HAMCMC instead of SGLD's isotropic updatesHAMCMC · Linear Gaussian Model, D=10 and D=100squared posterior-mean estimation errorHelped
Use HAMCMC with M=3 instead of SGLD or PSGLDLinear Gaussian Model, D=10 and D=100 · Linear Gaussian Modelsquared posterior-mean estimation errorHelped
Use HAMCMC instead of SGRLDLinear Gaussian Model, D=10 and D=100 · Linear Gaussian Modelsquared posterior-mean estimation error versus wall-clock timeMixed
Use HAMCMC instead of SGLD or PSGLDAlpha-Stable Matrix Factorization · Speech enhancement, test set at mixture SNR 5dBSDRHelped
Use HAMCMC instead of DSGLD or distributed PSGLDDistributed matrix factorization · MovieLens 1M test setRMSEHelped

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