arXiv (All)
open access
Acceleration for Affine-coupling problems
Saddle-point problems play an important role in modern machine learning, including robust optimization and algorithmic fairness. We investigate structured convex--concave minimax problems where the primal variable lies in a high-dimensional, unconstrained space $\mathbb{R}^d$, while the dual variabl
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
- On the Expressive Power of Sparse Geometric MPNNs#665453
- On the Expressive Power of Sparse Geometric MPNNs#663953
- Low solution rank of the matrix LASSO under RIP with consequences for rank-constrained algorithms#144202
- Convex Optimization#6060
- Sparse Convexification for High-Dimensional Constrained Regression#618101
Record · ID 1132198
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