Papers Distributed Optimization
“Distributed Optimization” 태그가 달린 논문 601편 · 필터 해제
Distributed Optimization for Massive Connectivity
Massive device connectivity in Internet of Thing (IoT) networks with sporadic traffic poses significant communication challenges. To overcome this challenge, the serving base station is required to detect the active devi…
Action DetectionActivity DetectionDistributed OptimizationALADIN-$α$ -- An open-source MATLAB toolbox for distributed non-convex optimization
This paper introduces an open-source software for distributed and decentralized non-convex optimization named ALADIN-$\alpha$. ALADIN-$\alpha$ is a MATLAB implementation of tailored variants of the Augmented Lagrangian A…
Distributed OptimizationMANGO: A Python Library for Parallel Hyperparameter Tuning
Tuning hyperparameters for machine learning algorithms is a tedious task, one that is typically done manually. To enable automated hyperparameter tuning, recent works have started to use techniques based on Bayesian opti…
Bayesian OptimizationBIG-bench Machine LearningDistributed ComputingDistributed Optimization+2Recurrent Averaging Inequalities in Multi-Agent Control and Social Dynamics Modeling
Many multi-agent control algorithms and dynamic agent-based models arising in natural and social sciences are based on the principle of iterative averaging. Each agent is associated to a value of interest, which may repr…
Distributed OptimizationFedSplit: An algorithmic framework for fast federated optimization
Motivated by federated learning, we consider the hub-and-spoke model of distributed optimization in which a central authority coordinates the computation of a solution among many agents while limiting communication. We f…
Distributed OptimizationFederated LearningDistributed Resource Allocation Algorithms for Multi-Operator Cognitive Communication Systems
We address the problem of resource allocation (RA) in a cognitive radio (CR) communication system with multiple secondary operators sharing spectrum with an incumbent primary operator. The key challenge of the RA problem…
Distributed OptimizationCommunication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
In this paper, we study distributed algorithms for large-scale AUC maximization with a deep neural network as a predictive model. Although distributed learning techniques have been investigated extensively in deep learni…
Distributed OptimizationPrivacy-Preserving Distributed Optimization via Subspace Perturbation: A General Framework
As the modern world becomes increasingly digitized and interconnected, distributed signal processing has proven to be effective in processing its large volume of data. However, a main challenge limiting the broad use of …
Distributed OptimizationPrivacy PreservingSupervised MPC control of large-scale electricity networks via clustering methods
This paper describes a control approach for large-scale electricity networks, with the goal of efficiently coordinating distributed generators to balance unexpected load variations with respect to nominal forecasts. To m…
ClusteringDistributed OptimizationStochaLM: a Stochastic alternate Linearization Method for distributed optimization
We present the Stochastic alternate Linearization Method (StochaLM), a token-based method for distributed optimization. This algorithm finds the solution of a consensus optimization problem by solving a sequence of subpr…
Distributed OptimizationFederated LearningUncertain Multi-Agent Systems with Distributed Constrained Optimization Missions and Event-Triggered Communications: Application to Resource Allocation
This paper deals with solving distributed optimization problems with equality constraints by a class of uncertain nonlinear heterogeneous dynamic multi-agent systems. It is assumed that each agent with an uncertain dynam…
Distributed OptimizationDC-DistADMM: ADMM Algorithm for Constrained Distributed Optimization over Directed Graphs
This article reports an algorithm for multi-agent distributed optimization problems with a common decision variable, local linear equality and inequality constraints and set constraints with convergence rate guarantees. …
Distributed OptimizationDistributed and time-varying primal-dual dynamics via contraction analysis
In this note, we provide an overarching analysis of primal-dual dynamics associated to linear equality-constrained optimization problems using contraction analysis. For the well-known standard version of the problem: we …
Distributed OptimizationIterative Pre-Conditioning to Expedite the Gradient-Descent Method
This paper considers the problem of multi-agent distributed optimization. In this problem, there are multiple agents in the system, and each agent only knows its local cost function. The objective for the agents is to co…
Distributed OptimizationCommunication-efficient Variance-reduced Stochastic Gradient Descent
We consider the problem of communication efficient distributed optimization where multiple nodes exchange important algorithm information in every iteration to solve large problems. In particular, we focus on the stochas…
Distributed OptimizationQuantizationDeep Reinforcement Learning for QoS-Constrained Resource Allocation in Multiservice Networks
In this article, we study a Radio Resource Allocation (RRA) that was formulated as a non-convex optimization problem whose main aim is to maximize the spectral efficiency subject to satisfaction guarantees in multiservic…
Deep Reinforcement LearningDistributed Optimizationreinforcement-learningReinforcement Learning+1Decentralized gradient methods: does topology matter?
Consensus-based distributed optimization methods have recently been advocated as alternatives to parameter server and ring all-reduce paradigms for large scale training of machine learning models. In this case, each work…
Distributed OptimizationRevisiting EXTRA for Smooth Distributed Optimization
EXTRA is a popular method for dencentralized distributed optimization and has broad applications. This paper revisits EXTRA. First, we give a sharp complexity analysis for EXTRA with the improved $O\left(\left(\frac{L}{\…
Distributed OptimizationMulti-frequency calibration for DOA estimation with distributed sensors
In this work, we investigate direction finding in the presence of sensor gain uncertainties and directional perturbations for sensor array processing in a multi-frequency scenario. Specifically, we adopt a distributed op…
Computational EfficiencyDistributed OptimizationImproving Rate of Convergence via Gain Adaptation in Multi-Agent Distributed ADMM Framework
In this paper, the alternating direction method of multipliers (ADMM) is investigated for distributed optimization problems in a networked multi-agent system. In particular, a new adaptive-gain ADMM algorithm is derived …
Distributed Optimization