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Research map / Probabilistic and scientific modeling / Variational and generative sampling

Zonotope Hit-and-run for Efficient Sampling from Projection DPPs

ICML 2017 · Probabilistic and scientific modeling › Variational and generative sampling · approach: Hamiltonian Monte Carlo · 6 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use hit-and-run moves over the zonotope instead of local basis-exchange movesProjection DPP sampling · Complete graph K_{10} and BA(20,2)mixing per iterationHelped
Use hit-and-run moves over the zonotope instead of local basis-exchange movesProjection DPP sampling · Complete graph K_{10} and BA(20,2)mixing per wall-clock time: more than 10^6 iterations compared to roughly 50 000 stepsNo clear effect
Use hit-and-run moves over the zonotope instead of local basis-exchange movesProjection DPP sampling · Text summarizationdifferent summaries explored: about 50% against 10%Helped
Use hit-and-run moves over the zonotope instead of local basis-exchange movesProjection DPP sampling · Text summarizationvariance of estimatesHelped

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