arXiv (All)
open access
Forward Tangent-Centered Sinkhorn DRO: Exact Nominal Recovery from Optimal Transport to KL
Fixed-reference entropy-regularized transport yields smooth distributionally robust optimization (DRO) objectives, but its value as a function of the adversarial marginal is generally minimized at a kernel-smoothed law rather than at the nominal distribution. Consequently, the smallest raw ambiguity
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Risk-Controlled DFT Selection for Machine-Learned Interatomic Potentials#1354320
- What Does a Semilocal Machine-Learning Correction Actually Learn? Size-Dependent Errors across Four Parent Functionals#1141890
- CertMoE: Robustness Certification for Mixture-of-Experts LLMs via Routing-Aware Smoothing#1414000
- CertMoE: Robustness Certification for Mixture-of-Experts LLMs via Routing-Aware Smoothing#1406386
- Drive-Field Information Theory. A Holographic Entropic Model for Emergent Gravity#118840
Record · ID 1422936
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive