arXiv (All)
open access
SURF: Steering the Scalarization Weight to Uniformly Traverse the Pareto Front
Scalarization is widely used in multi-objective optimization owing to its simplicity and scalability. In many applications, the goal is to generate solutions that represent diverse user preferences, ideally with uniform coverage of the Pareto front (PF). However, uniformly sampling scalarization wei
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
- DCM Bandits: Multiplayer Information Asymmetric Cascading Bandits for Multiple Clicks#447964
- A practical approach to subset selection for multi-objective optimization via simulation#181131
- Breaking the 1/3 Barrier for constrained $\boldsymbol{k}$-Submodular Maximization: A Proportional Top-2 Randomized Framework#1297241
- Converge Then Diversify: Decoupling Convergence and Diversity in Multi-Objective Bayesian Optimisation#1071189
- Xronos: Heterogeneity-Aware Tensor Parallelism for Collaborative LLM Fine-Tuning on Edge CPUs#1014955
Record · ID 1298077
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