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Operations Research

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Operations Research

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Research Frontiers in Distributed Optimization Networks

Design of decentralized algorithms for multi-agent systems to achieve global optimization objectives through local computation and communication.

Asynchronous Consensus in Heterogeneous Agent Networks
Gradient Compression and Information Loss Tradeoffs
Byzantine-Resilient Distributed Learning at Scale
Federated Optimization with Stragglers and Dropouts
Privacy-Preserving Decomposition in Multi-Agent Systems
Non-Convex Distributed Optimization Landscape Analysis
Incentive Alignment in Decentralized Resource Allocation
Communication-Constrained Coordination in Dynamic Graphs
Gossip Algorithms for Heterogeneous Convergence Rates
Distributed Optimization Under Adversarial Network Perturbations

All Operations Research PhD categories