pytorch implementation of Optimization as a Model for Few-shot Learning
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Updated
Feb 26, 2019 - Python
pytorch implementation of Optimization as a Model for Few-shot Learning
[IEEE TSIPN' 2022] "Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks", by Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Wenqing Zheng, Zhangyang Wang, Alejandro Ribeiro, and Brian M. Sadler
source code of AISTATS 2020 paper: Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs
Device-to-Device (D2D) and assocaited Federated Learning simulation in Python using Pytorch for Learning operations. Implemented simultaneous operation of multiple FL modes.
Investigating the reproducibility of federated GNN models
The official implementation of the paper "Topology-aware Generalization of Decentralized SGD"
Decentralized and Privacy-Preserving Machine Learning: Exploring the Power of Federated Learning.
code for "Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence"
[ICML 2023] Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
Handwritten Digit Classification using Federated Learning
Breaching privacy in federated learning scenarios for vision and text
[TMLR] CoDeC: Communication-Efficient Decentralized Continual Learning
subMFL: Compatible subModel Generation for Federated Learning in Device Heterogeneous Environment
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