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Distributed Optimization

The goal of Distributed Optimization is to optimize a certain objective defined over millions of billions of data that is distributed over many machines by utilizing the computational power of these machines.

Source: Analysis of Distributed StochasticDual Coordinate Ascent

Papers

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Showing 251–300 of 536 papers

TitleStatusHype
Towards privacy-preserving cooperative control via encrypted distributed optimization—0
Towards Scalable Multi-View Reconstruction of Geometry and Materials—0
Fairness-Oriented User Scheduling for Bursty Downlink Transmission Using Multi-Agent Reinforcement Learning—0
Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent—0
Training Deep Neural Networks via Optimization Over Graphs—0
Trajectory Normalized Gradients for Distributed Optimization—0
Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs—0
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?—0
Uncertain Multi-Agent Systems with Distributed Constrained Optimization Missions and Event-Triggered Communications: Application to Resource Allocation—0
Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective—0
Utilizing Redundancy in Cost Functions for Resilience in Distributed Optimization and Learning—0
Variance Reduction in Deep Learning: More Momentum is All You Need—0
vqSGD: Vector Quantized Stochastic Gradient Descent—0
When Evolutionary Computation Meets Privacy—0
Widely-distributed Radar Imaging Based on Consensus ADMM—0
Without-Replacement Sampling for Stochastic Gradient Methods: Convergence Results and Application to Distributed Optimization—0
Without-Replacement Sampling for Stochastic Gradient Methods—0
Asynchronous Message-Passing and Zeroth-Order Optimization Based Distributed Learning with a Use-Case in Resource Allocation in Communication Networks—0
Zeroth-Order Feedback-Based Optimization for Distributed Demand Response—0
Zeroth Order Nonconvex Multi-Agent Optimization over Networks—0
Distributed Optimization for Over-Parameterized Learning—0
Distributed Optimization for Quadratic Cost Functions over Large-Scale Networks with Quantized Communication and Finite-Time Convergence—0
Distributed Optimization for Reactive Power Sharing and Stability of Inverter-Based Resources Under Voltage Limits—0
Distributed Optimization for Smart Cyber-Physical Networks—0
Distributed Optimization for Traffic Light Control and Connected Automated Vehicle Coordination in Mixed-Traffic Intersections—0
Distributed Optimization in Distribution Systems with Grid-Forming and Grid-Supporting Inverters—0
Distributed optimization in wireless sensor networks: an island-model framework—0
Distributed Optimization of Convex Sum of Non-Convex Functions—0
Distributed Optimization of Graph Convolutional Network using Subgraph Variance—0
Distributed Optimization over Block-Cyclic Data—0
Distributed Optimization Strategy for Multi Area Economic Dispatch Based on Electro Search Optimization Algorithm—0
Distributed Optimization via Energy Conservation Laws in Dilated Coordinates—0
Distributed Optimization via Gradient Descent with Event-Triggered Zooming over Quantized Communication—0
Distributed Optimization via Kernelized Multi-armed Bandits—0
Distributed Optimization with Efficient Communication, Event-Triggered Solution Enhancement, and Operation Stopping—0
Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement—0
Distributed Optimization with Gradient Tracking over Heterogeneous Delay-Prone Directed Networks—0
Distributed Personalized Gradient Tracking with Convex Parametric Models—0
Distributed Pose Graph Optimization using the Splitting Method based on the Alternating Direction Method of Multipliers—0
Distributed Privacy-Preserving Electric Vehicle Charging Control Based on Secret Sharing—0
Distributed Random Reshuffling Methods with Improved Convergence—0
Distributed Random Reshuffling over Networks—0
Distributed Resource Allocation Algorithms for Multi-Operator Cognitive Communication Systems—0
Distributed saddle point problems for strongly concave-convex functions—0
Distributed Second Order Methods with Fast Rates and Compressed Communication—0
Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Bounds—0
Distributed Stochastic Consensus Optimization with Momentum for Nonconvex Nonsmooth Problems—0
Distributed Stochastic Variance Reduced Gradient Methods and A Lower Bound for Communication Complexity—0
Distributed System Identification for Linear Stochastic Systems with Binary Sensors—0
Distributed Traffic Signal Control via Coordinated Maximum Pressure-plus-Penalty—0
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