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Optimal distributed stochastic mirror descent for strongly convex optimization
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization
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Initialization-free distributed algorithms for optimal resource allocation with feasibility constraints and application to economic dispatch of power systems
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Mirror descent and nonlinear projected subgradient methods for convex optimization
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Distributed strongly convex optimization
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Subgradient methods and consensus algorithms for solving convex optimization problems
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Distributed Subgradient Methods for Multi-Agent Optimization
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Constrained Consensus and Optimization in Multi-Agent Networks
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Gossip Algorithms for Convex Consensus Optimization Over Networks
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On Distributed Convex Optimization Under Inequality and Equality Constraints
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Distributed Constrained Optimization by Consensus-Based Primal-Dual Perturbation Method
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Regularized Primal–Dual Subgradient Method for Distributed Constrained Optimization
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Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks
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Robust Stochastic Approximation Approach to Stochastic Programming
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EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization
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On Convergence Rate of Distributed Stochastic Gradient Algorithm for Convex Optimization with Inequality Constraints
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Distributed optimization in sensor networks
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Continuous-time Distributed Convex Optimization with Set Constraints
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Gradient-free distributed optimization and nash equilibrium seeking
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Communication-Efficient Distributed Strongly Convex Stochastic Optimization: Non-Asymptotic Rates
inferred← citeshttps://doi.org/10.48550/arxiv.1810.11568openalex-snapshot
Distributed Stochastic Approximation for Solving Network Optimization Problems Under Random Quantization
inferred← citeshttps://doi.org/10.48550/arxiv.1901.00214openalex-snapshot
Clustering with Distributed Data
inferred← citeshttps://doi.org/10.48550/arxiv.1912.13222openalex-snapshot
Distributed Stochastic Block Coordinate Descent for Time-Varying Multi-Agent Optimization
inferred← citeshttps://doi.org/10.48550/arxiv.2002.03269openalex-snapshot
Linearly Convergent Algorithm with Variance Reduction for Distributed Stochastic Optimization
inferred← citeshttps://doi.org/10.48550/arxiv.2003.06949openalex-snapshot
RC Circuits based Distributed Conditional Gradient Method
inferred← citeshttps://doi.org/10.48550/arxiv.2009.06747openalex-snapshot
Distributed Mirror Descent with Integral Feedback: Asymptotic Convergence Analysis of Continuous-time Dynamics
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