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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 201–225 of 536 papers

TitleStatusHype
Distributed Mirror Descent with Integral Feedback: Asymptotic Convergence Analysis of Continuous-time Dynamics—0
Distributed Model Predictive Control with Reconfigurable Terminal Ingredients for Reference Tracking—0
Distributed model predictive control without terminal cost under inexact distributed optimization—0
Parallel Momentum Methods Under Biased Gradient Estimations—0
Differentially Private Consensus-Based Distributed Optimization—0
Distributed-MPC with Data-Driven Estimation of Bus Admittance Matrix in Voltage Control—0
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs—0
Distributed Nesterov gradient methods over arbitrary graphs—0
Adaptive Sampling Distributed Stochastic Variance Reduced Gradient for Heterogeneous Distributed Datasets—0
Distributed Newton-like Algorithms and Learning for Optimized Power Dispatch—0
Accelerated Distributed Optimization with Compression and Error Feedback—0
GTAdam: Gradient Tracking with Adaptive Momentum for Distributed Online Optimization—0
Distributed Online Optimization with Byzantine Adversarial Agents—0
Detecting Shared Data Manipulation in Distributed Optimization Algorithms—0
Distributed Optimization for Client-Server Architecture with Negative Gradient Weights—0
Distributed Optimization for Massive Connectivity—0
Design of heterogeneous multi-agent system for distributed computation—0
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning—0
Delayed Projection Techniques for Linearly Constrained Problems: Convergence Rates, Acceleration, and Applications—0
Distributed Optimization for Reactive Power Sharing and Stability of Inverter-Based Resources Under Voltage Limits—0
Deep Reinforcement Learning for QoS-Constrained Resource Allocation in Multiservice Networks—0
Distributed Optimization for Traffic Light Control and Connected Automated Vehicle Coordination in Mixed-Traffic Intersections—0
BALPA: A Balanced Primal-Dual Algorithm for Nonsmooth Optimization with Application to Distributed Optimization—0
Distributed optimization in wireless sensor networks: an island-model framework—0
A Mirror Descent-Based Algorithm for Corruption-Tolerant Distributed Gradient Descent—0
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