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Found 12 papers, 2 papers with code
ReCo: A Dataset for Residential Community Layout Planning
In order to address the issues and advance a benchmark dataset for various intelligent spatial design and analysis applications in the development of smart city, we introduce Residential Community Layout Planning (ReCo) Dataset, which is the first and largest open-source vector dataset related to real-world community to date.
Asynchronous Parallel Incremental Block-Coordinate Descent for Decentralized Machine Learning
This paper studies the problem of training an ML model over decentralized systems, where data are distributed over many user devices and the learning algorithm run on-device, with the aim of relaxing the burden at a central entity/server.
Adaptive Stochastic ADMM for Decentralized Reinforcement Learning in Edge Industrial IoT
Alternating direction method of multipliers (ADMM) has a structure that allows for decentralized implementation, and has shown faster convergence than gradient descent based methods.
Coded Stochastic ADMM for Decentralized Consensus Optimization with Edge Computing
A class of mini-batch stochastic alternating direction method of multipliers (ADMM) algorithms is explored to develop the distributed learning model.
Fully Decentralized Federated Learning Based Beamforming Design for UAV Communications
To handle the data explosion in the era of internet of things (IoT), it is of interest to investigate the decentralized network, with the aim at relaxing the burden to central server along with keeping data privacy.
Signal Processing
Decentralized Beamforming Design for Intelligent Reflecting Surface-enhanced Cell-free Networks
Cell-free networks are considered as a promising distributed network architecture to satisfy the increasing number of users and high rate expectations in beyond-5G systems.
Odd-even layer-number effect and layer-dependent magnetic phase diagrams in MnBi2Te4
However, the layer-dependent magnetism of MnBi2Te4, which is fundamental and crucial for further exploration of quantum phenomena in this system, remains elusive.
Materials Science
Learning Based Hybrid Beamforming for Millimeter Wave Multi-User MIMO Systems
Hybrid beamforming (HBF) design is a crucial stage in millimeter wave (mmWave) multi-user multi-input multi-output (MU-MIMO) systems.
Learning Based Hybrid Beamforming Design for Full-Duplex Millimeter Wave Systems
We propose two learning schemes to design HBF for FD mmWave systems, i. e., extreme learning machine based HBF (ELM-HBF) and convolutional neural networks based HBF (CNN-HBF).
Mobility-aware Content Preference Learning in Decentralized Caching Networks
To determine the caching scheme for decentralized caching networks, the content preference learning problem based on mobility prediction is studied.
Decentralized Multi-Task Learning Based on Extreme Learning Machines
We first present the ELM based MTL problem in the centralized setting, which is solved by the proposed MTL-ELM algorithm.
Local Differential Privacy in Decentralized Optimization
Privacy concerns with sensitive data are receiving increasing attention.
