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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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3 results for “Sinkhorn-EM”

Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transportstat.ML

sEM uses optimal transport to improve EM algorithm for better convergence and avoiding local optima.

problem Improving the EM algorithm for better convergence and avoiding local optima.

method sEM uses entropic optimal transport to compute responsibilities in the expectation step, leading to better global convergence guarantees and avoiding local optima.

result sEM learns cell labels significantly better than other approaches, improving convergence and avoiding local optima.

EM algorithm optimal transport sinkhorn divergence convergence local optima

2020-06-30abs ↗pdf ↗

On Model-Based Clustering With Entropic Optimal Transportstat.ME

New method optimizes clustering with better log-likelihood landscape.

problem Nonconvex log-likelihood optimization in model-based clustering.

method Entropic optimal transport loss for Sinkhorn-EM algorithm.

result New loss function avoids spurious local optima.

clustering model-based log-likelihood optimal transport Sinkhorn-EM

2026-05-05abs ↗pdf ↗

Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EMmath.OC

The paper analyzes mirror descent in measure spaces and its applications.

problem Optimizing convex functionals over measure spaces.

method Derives convergence of mirror descent for relatively smooth and convex pairs of functionals.

result Shows Sinkhorn's primal iterations and EM as mirror descent.

mirror descent measure spaces Sinkhorn EM convex optimization

2022-06-17abs ↗pdf ↗