An Overview of Autonomous Connection Establishment Methods in Peer-to-Peer Deep Learning
The exchange of model parameters between peers is critical in peer-to-peer deep learning.
Historically, connections between agents were assigned randomly based on network …
Historically, connections between agents were assigned randomly based on network …
Federated learning with non-iid data: A survey
Z Lu, H Pan, Y Dai, X Si, Y Zhang - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Federated learning (FL) is an efficient decentralized machine learning methodology for
processing nonindependent and identically distributed (non-IID) data due to geographical …
processing nonindependent and identically distributed (non-IID) data due to geographical …
Feature distribution matching for federated domain generalization
Multi-source domain adaptation has been intensively studied. The distribution shift in
features inherent to specific domains causes the negative transfer problem, degrading a …
features inherent to specific domains causes the negative transfer problem, degrading a …
[HTML][HTML] Zero time waste in pre-trained early exit neural networks
The problem of reducing processing time of large deep learning models is a fundamental
challenge in many real-world applications. Early exit methods strive towards this goal by …
challenge in many real-world applications. Early exit methods strive towards this goal by …
A novel physical activity recognition approach using deep ensemble optimized transformers and reinforcement learning
In recent years, human physical activity recognition has increasingly attracted attention from
different research fields such as healthcare, computer-human interaction, lifestyle …
different research fields such as healthcare, computer-human interaction, lifestyle …
Optimizing Proximity Strategy for Federated Learning Node Selection in the Space-Air-Ground Information Network for Smart Cities
W Wang, P Li, S Li, J Zhang, Z Zhou… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
As the Internet of Things (IoT) technology and Artificial Intelligence (AI) technology continue
to evolve, many envisaged concepts regarding smart cities are gradually becoming a reality …
to evolve, many envisaged concepts regarding smart cities are gradually becoming a reality …
FedMCSA: Personalized federated learning via model components self-attention
Federated learning (FL) facilitates multiple clients to jointly train a machine learning model
without sharing their private data. However, heterogeneous data that is not independent and …
without sharing their private data. However, heterogeneous data that is not independent and …
Meta learning in decentralized neural networks: towards more general AI
Y Sun - Proceedings of the AAAI Conference on Artificial …, 2023 - ojs.aaai.org
Meta-learning usually refers to a learning algorithm that learns from other learning
algorithms. The problem of uncertainty in the predictions of neural networks shows that the …
algorithms. The problem of uncertainty in the predictions of neural networks shows that the …
Meta Neural Coordination
Y Sun - arXiv preprint arXiv:2305.12109, 2023 - arxiv.org
Meta-learning aims to develop algorithms that can learn from other learning algorithms to
adapt to new and changing environments. This requires a model of how other learning …
adapt to new and changing environments. This requires a model of how other learning …
Methods and Prospects of Personalized Federated Learning.
SUN Yanhua, W Zihang, LIU Chang… - Journal of …, 2024 - search.ebscohost.com
Currently, with the advancement of artificial intelligence research, artificial intelligence is
being widely adopted, and the increasing demand in areas such as data governance has …
being widely adopted, and the increasing demand in areas such as data governance has …