Pages that link to "Item:Q2020611"

The following pages link to Distributed stochastic gradient tracking methods (Q2020611):

Displaying 32 items.

• Incremental without replacement sampling in nonconvex optimization (Q2046568) (← links)
• Distributed gradient tracking methods with finite data rates (Q2070027) (← links)
• Projected subgradient based distributed convex optimization with transmission noises (Q2073071) (← links)
• Convergence results of a nested decentralized gradient method for non-strongly convex problems (Q2082236) (← links)
• An accelerated distributed gradient method with local memory (Q2097691) (← links)
• Tracking-ADMM for distributed constraint-coupled optimization (Q2184513) (← links)
• Convergence of distributed gradient-tracking-based optimization algorithms with random graphs (Q2235622) (← links)
• Exact spectral-like gradient method for distributed optimization (Q2282815) (← links)
• Zeroth-order feedback optimization for cooperative multi-agent systems (Q2682294) (← links)
• Generalized multi-cluster game under partial-decision information with applications to management of energy Internet (Q2694163) (← links)
• Distributed stochastic gradient tracking methods with momentum acceleration for non-convex optimization (Q2696917) (← links)
• Computation of exact gradients in distributed dynamic systems (Q4391288) (← links)
• (Q4998051) (← links)
• Fast Decentralized Nonconvex Finite-Sum Optimization with Recursive Variance Reduction (Q5026835) (← links)
• (Q5149230) (← links)
• An Optimal Algorithm for Decentralized Finite-Sum Optimization (Q5162661) (← links)
• An event-triggering algorithm for decentralized stochastic optimization over networks (Q6053824) (← links)
• Improving the Transient Times for Distributed Stochastic Gradient Methods (Q6080216) (← links)
• Gradient-Tracking-Based Distributed Optimization With Guaranteed Optimality Under Noisy Information Sharing (Q6093202) (← links)
• Graph Topology Invariant Gradient and Sampling Complexity for Decentralized and Stochastic Optimization (Q6116247) (← links)
• Decentralized Bayesian learning with Metropolis-adjusted Hamiltonian Monte Carlo (Q6134345) (← links)
• Distributed Personalized Gradient Tracking With Convex Parametric Models (Q6137545) (← links)
• Gradient-tracking based differentially private distributed optimization with enhanced optimization accuracy (Q6165323) (← links)
• Event-triggered primal-dual design with linear convergence for distributed nonstrongly convex optimization (Q6177284) (← links)
• Distributed projection‐free algorithm for constrained aggregative optimization (Q6193171) (← links)
• Confidence region for distributed stochastic optimization problem via stochastic gradient tracking method (Q6537307) (← links)
• Distributed constrained optimization with periodic dynamic quantization (Q6537317) (← links)
• A unified momentum-based paradigm of decentralized SGD for non-convex models and heterogeneous data (Q6579292) (← links)
• Distributed predefined-time constrained social cost minimization problem under the partial information setting (Q6590435) (← links)
• Stochastic mirror descent for convex optimization with consensus constraints (Q6598411) (← links)
• Balancing communication and computation in gradient tracking algorithms for decentralized optimization (Q6655816) (← links)
• An accelerated decentralized stochastic optimization algorithm with inexact model (Q6664887) (← links)