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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 151–175 of 536 papers

TitleStatusHype
Distributed Algorithms for Feature Extraction Off-loading in Multi-Camera Visual Sensor Networks—0
Byzantine Fault Tolerant Distributed Linear Regression—0
An Equivalent Circuit Approach to Distributed Optimization—0
Discretized Distributed Optimization over Dynamic Digraphs—0
Diffusion Adaptation over Networks—0
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning—0
Differentially-Private Distributed Model Predictive Control of Linear Discrete-Time Systems with Global Constraints—0
Differentially Private Distributed Convex Optimization—0
Differentially Private Consensus-Based Distributed Optimization—0
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs—0
Adaptive Sampling Distributed Stochastic Variance Reduced Gradient for Heterogeneous Distributed Datasets—0
Accelerated Distributed Optimization with Compression and Error Feedback—0
Detecting Shared Data Manipulation in Distributed Optimization Algorithms—0
DiLoCo: Distributed Low-Communication Training of Language Models—0
Design of heterogeneous multi-agent system for distributed computation—0
Distributed Continuous-Time Optimization with Uncertain Time-Varying Quadratic Cost Functions—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 and time-varying primal-dual dynamics via contraction analysis—0
Distributed Asynchronous Dual Free Stochastic Dual Coordinate Ascent—0
Deep Reinforcement Learning for QoS-Constrained Resource Allocation in Multiservice Networks—0
Distributed Collision-Free Motion Coordination on a Sphere: A Conic Control Barrier Function Approach—0
Distributed Convex Optimization With Limited Communications—0
Distributed Convex Optimization with State-Dependent (Social) Interactions over Random Networks—0
BALPA: A Balanced Primal-Dual Algorithm for Nonsmooth Optimization with Application to Distributed Optimization—0
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