arXiv (All)
open access
Global solutions for the sensors placement problem via weakly convex optimization
We address the problem of optimally placing a limited number of sensors to reconstruct high-dimensional signals without knowledge of the underlying dynamics. The task is formulated as a nonconvex combinatorial optimisation problem and recast as a weakly convex constrained projection problem. This re
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
- Convex optimization for data science : continuous-time Lyapunov analyses, geometry dependent matching pursuit and concentration inequalities#274337
- FlockDiffusion: Assignment-Conditioned Diffusion for Multi-Drone Task Allocation and Completion#1049480
- Convex Envelopes for Low Rank Approximation#319027
- Riemannian Difference-of-Convex Optimization for K-Means Clustering#1119383
- FlipToSee: A Probabilistic Stable Placement Prior for Active Visual Exploration via Regrasping#1033856
Record · ID 974498
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