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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.

169,341 papers · 148 categories

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4 results for “elliptope”

cCorrGAN: Conditional Correlation GAN for Learning Empirical Conditional Distributions in the Elliptopeq-fin.ST

cCorrGAN approximates conditional correlation matrices using GANs.

problem Learning empirical conditional distributions in the elliptope of correlation matrices.

method Conditional Generative Adversarial Networks (GANs) applied to correlation matrices.

result Validated through Monte Carlo simulations in finance.

GANs correlation matrices empirical distributions elliptope geometry

2021-07-22abs ↗pdf ↗

A Grothendieck-type inequality for local maximamath.OC

This paper proves that local maxima in a non-convex optimization problem are close to the SDP optimum.

problem Optimization problems with a large number of local maxima.

method Proving that all local maxima are within a small gap from the SDP optimum for the elliptope problem.

result Local maxima are within a small gap from the SDP optimum, and arbitrarily small relative error can be achieved with a rank constraint of order one.

Grothendieck inequality local maxima elliptope semidefinite programming optimization

2016-03-13abs ↗pdf ↗

Theoretically and computationally convenient geometries on full-rank correlation matricesmath.DG

New metrics defined for full-rank correlation matrices, ensuring unique operations.

problem No suitable problem statement as the abstract does not describe a problem to be solved.

method New Riemannian metrics defined on full-rank correlation matrices, providing unique operations.

result Unique Riemannian logarithm and Fréchet mean defined for full-rank correlation matrices.

full-rank correlation matrices Riemannian metrics unique operations Lie group affine-invariant metric

2022-01-17abs ↗pdf ↗

Graph-Based Correlation Matrix Generation: A Convex Optimization Approachstat.ML

Generates correlation matrices with specific graph structures using convex optimization.

problem Creating theoretical correlation matrices with prescribed graph structures.

method Convex optimization framework projecting an initial matrix onto an elliptope with positive semidefiniteness constraint.

result The approach offers greater flexibility in generating correlation matrices with controlled mean of off-diagonal entries.

correlation matrix graph-based convex optimization matrix completion sparsity

2026-07-24abs ↗pdf ↗