The paper proposes a new optimization method that is based on sampling latent variables. Their approach is based on constructing a optimal Voronoi tessellation that leads to biased but variance free gradient estimates. Strengths: - approach can be implemented in probabillistic programming languages Weaknesses: - comparisons with variance-reduced MC-VI methods are missing