Pinned Repositories
202112-WXTX
NAIC2021 AI+无线通信
CGL-GAN
A distributed learning algorithm for GANs with Non-IID dataset
ClusterFL
Repo for MobiSys 2021 paper: "ClusterFL: A Similarity-Aware Federated Learning System for Human Activity Recognition".
Communication_Modulation
This repository provides a simple python script for getting experience with common modulation techniques i.e. QAM, PSK, ASK and BPSK
eat_pytorch_in_20_days
Pytorch🍊🍉 is delicious, just eat it! 😋😋
Fed-TDA
The implementation of our paper Fed-TDA
FedDyn
federated-minimax
FedGDA-GT
FedGDA-GT: A communication-efficient algorithm with linear convergence under federated minimax learning
Wireless-Communication-Simulation
Simulate the real wireless communication environment and compare the modulation performances of BPSK, QPSK, 16QAM, 64QAM.
superjdz's Repositories
superjdz/Wireless-Communication-Simulation
Simulate the real wireless communication environment and compare the modulation performances of BPSK, QPSK, 16QAM, 64QAM.
superjdz/202112-WXTX
NAIC2021 AI+无线通信
superjdz/CGL-GAN
A distributed learning algorithm for GANs with Non-IID dataset
superjdz/ClusterFL
Repo for MobiSys 2021 paper: "ClusterFL: A Similarity-Aware Federated Learning System for Human Activity Recognition".
superjdz/Communication_Modulation
This repository provides a simple python script for getting experience with common modulation techniques i.e. QAM, PSK, ASK and BPSK
superjdz/eat_pytorch_in_20_days
Pytorch🍊🍉 is delicious, just eat it! 😋😋
superjdz/Fed-TDA
The implementation of our paper Fed-TDA
superjdz/FedDyn
superjdz/federated-minimax
superjdz/FedGDA-GT
FedGDA-GT: A communication-efficient algorithm with linear convergence under federated minimax learning
superjdz/FSL-GAN
Repository for FSL-GAN
superjdz/MTFL-For-Personalised-DNNs
Code for 'Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing', published in IEEE TPDS.
superjdz/numpy-ml
Machine learning, in numpy
superjdz/FedML-GradControl
Research project about Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating based on the article
superjdz/gnn-tutorial
Tutorial for NoF 2022: "Building Network Digital Twins for Next-Generation WLANs using Graph Neural Networks"
superjdz/HT-Fed-GAN
superjdz/Impact-of-Data-Freshness-in-Learning
This repository contains the coding materials to reproduce the learning error curves of the paper "How Does Data Freshness Affect Real-time Supervised Learning ?".
superjdz/InclusiveFL
superjdz/LinSpeedUpCode
Our code for the ICML 2022 submission : Linear Speedup in Personalized Collaborative Learning
superjdz/ML5G-PS-005
Digital-twin-enabled 6G: Depth Map Estimation in mmWave systems
superjdz/MonoFlow
superjdz/PFL
superjdz/pyprobml
Python code for "Machine learning: a probabilistic perspective" (2nd edition)
superjdz/PyramidFL
[ACM MobiCom 2022] " PyramidFL: Fine-grained Data and System Heterogeneity-aware Client Selection for Efficient Federated Learning" by Chenning Li, Xiao Zeng, Mi Zhang, and Zhichao Cao.
superjdz/RouteNet-Erlang
superjdz/sgda
Code for "Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods"
superjdz/superjdz.github.io
superjdz/TDGAN-PyTorch
Temporary Discriminator GAN
superjdz/UAGAN
Training Federated GANs with Theoretical Guarantees: AUniversal Aggregation Approach
superjdz/VAE_LSTM_Federated
FIL_VAE_LSTM_Fed