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Scaffold: Stochastic Controlled Averaging for Federated Learning
Federated learning has emerged as an important paradigm in modern large-scale machine learning. Unlike in traditional centralized learning where models are trained using large... -
Distributed Logistic Regression Problem
The dataset used in this paper is a distributed logistic regression problem. -
Cell Zooming with Masked Data for Off-Grid Small Cell Networks: Distributed O...
The dataset used in this paper is a set of parameters for simulating cell zooming with masked data for off-grid small cell networks. -
Generated dataset for distributed optimization
The dataset used in the paper is a generated dataset consisting of 10,000 samples randomly distributed to the nodes of a network of size 100. -
Ridge Regression Dataset
The dataset used in the paper is a synthetic dataset for ridge regression problem over a network of agents, modeled as a Erdos-Renyi graph with m = 30 nodes and edge probability... -
Quantization of Distributed Data for Learning
The dataset used in this paper is a distributed dataset for learning, where the data is distributed over a trusted network and the communication constraints can create a... -
Distributed Stochastic Gradient Descent (DSGD) dataset
The dataset used in the paper is a network of n nodes, where each node holds a local copy of the decision vector zi. -
Compressed Regression over Adaptive Networks
The dataset used in the paper is a network of distributed agents that solve a regression problem. The agents employ the ACTC diffusion strategy, which involves adaptive...
