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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.

168,657 papers · 148 categories

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7 results for “density-power-divergences”

A Unified Representation of Density-Power-Based Divergences Reducible to M-Estimationcs.IT

Unified representation of density-power-based divergences simplifies estimation to M-estimation.

problem Outliers in density estimation.

method Define a norm-based Bregman density power divergence (NB-DPD) that reduces to M-estimation.

result NB-DPD connects and generalizes existing divergences, highlighting robustness properties.

density-power-divergences M-estimation robustness Bregman divergences outliers

2025-01-27abs ↗pdf ↗

Robust Principal Component Analysis using Density Power Divergencestat.ME

A new robust PCA estimator combining M-estimators and minimum divergence estimators.

problem Adverse effect of outlying observations in PCA for high-dimensional data.

method Minimum density power divergence estimator combined with a computationally efficient algorithm.

result High breakdown guarantee regardless of data dimension with theoretical support and practical applications.

PCA robustness density power divergence M-estimators dimensionality reduction

2023-09-24abs ↗pdf ↗

Relationship between Hölder Divergence and Functional Density Power Divergence: Intersection and Generalizationcs.IT

Study explores relationship between Hölder and FDPD divergences.

problem Understanding the relationship between Hölder and FDPD divergences.

method Intersection and generalization of divergence families, proving nonnegativity, deriving inequalities.

result Established

ξ

-Hölder divergence and derived inequalities.

Hölder divergence FDPD divergence families nonnegativity inequalities

2025-04-23abs ↗pdf ↗

Minimizing robust density power-based divergences for general parametric density modelsstat.ME

New method minimizes robust density power-based divergences for general parametric densities.

problem Computational complexity of minimizing DPD for general parametric densities.

method Stochastic approach to minimize DPD for general parametric density models.

result Proposed method can be applied to minimize other density power-based γ-divergences.

density power divergence robust estimation general parametric densities stochastic approach γ-divergences

2023-07-11abs ↗pdf ↗

Asymptotic breakdown point analysis of the minimum density power divergence estimator under independent non-homogeneous setupsmath.ST

Paper analyzes robustness of MDPDE under INH setups.

problem Global reliability and breakdown behavior of MDPDE under INH.

method Asymptotic breakdown point analysis of MDPDE.

result Derives a theoretical lower bound for the asymptotic breakdown point.

MDPDE asymptotic breakdown point robustness INH setups fixed design regression

2025-08-17abs ↗pdf ↗

Asymptotic Separability of Diffusion and Jump Components in High-Frequency CIR and CKLS Modelsq-fin.ST

Robustly detects jumps in high-frequency CIR and CKLS models.

problem Jump detection in high-frequency jump-diffusion processes.

method MDPDE-based robust estimators for drift and diffusion coefficients.

result Maximum of normalized residuals converges to Gumbel distribution.

jump detection high-frequency CIR model CKLS model MDPDE

2026-03-05abs ↗pdf ↗

Provably robust learning of regression neural networks using

β

-divergencesstat.ML

New robust learning framework for regression NNs using β-divergences.

problem Outliers and data contamination in regression NNs training.

method Proposes rRNet based on β-divergence for robust learning of regression NNs.

result rRNet achieves optimal 50% asymptotic breakdown point for all β ∈ (0, 1].

robust learning regression neural networks β-divergence influence functions asymptotic breakdown point

2026-02-09abs ↗pdf ↗