Networked Parallel Algorithms for Robust Convex Optimization via the Scenario Approach
From MaRDI portal
Publication:4625791
DOI10.1007/978-3-319-67068-3_25zbMath1457.90111OpenAlexW2477083526MaRDI QIDQ4625791
Publication date: 25 February 2019
Published in: Lecture Notes in Control and Information Sciences - Proceedings (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-319-67068-3_25
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Robust control of uncertain systems: classical results and recent developments
- Random algorithms for convex minimization problems
- Uncertain convex programs: randomized solutions and confidence levels
- Research on probabilistic methods for control system design
- Randomized algorithms for analysis and control of uncertain systems. With applications
- Randomized methods for design of uncertain systems: sample complexity and sequential algorithms
- Robust Convex Optimization
- Asynchronous Gossip-Based Random Projection Algorithms Over Networks
- Distributed Optimization Over Time-Varying Directed Graphs
- Distributed Continuous-Time Convex Optimization on Weight-Balanced Digraphs
- Random Convex Programs
- Theory and Applications of Robust Optimization
- The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs
- Distributed Convex Optimization with Inequality Constraints over Time-Varying Unbalanced Digraphs
- Networked Parallel Algorithms for Robust Convex Optimization via the Scenario Approach
- Distributed Subgradient Methods for Multi-Agent Optimization
- Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling
- Relaxations for Robust Linear Matrix Inequality Problems with Verifications for Exactness
- Distributed Random Convex Programming via Constraints Consensus
This page was built for publication: Networked Parallel Algorithms for Robust Convex Optimization via the Scenario Approach