lebeausc

Addressing-Class-Imbalance-FL

This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).

amc

[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

Asynchronous-Federated-Unlearning

A new scalable federated learning research framework

BalanceFL

Repo. for IPSN 2022 paper: "BalanceFL: Addressing Class Imbalance in Long-Tail Federated Learning".

CIM-Federated-Learning-Pytorch

DropEdge

This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

early_exit_calibration

early_exit_dnn_analysis

This code contains all code developed to analyze early-exit DNNs considering an edge-cloud architecture.

Edge-Computing-Dataset

MEC，Edge service, Edge Application, Service Computing.

EdgeViT

This is an unofficial PyTorch implementation of EdgeViT in "EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers", arXiv 2022.

FedBFPT

Game-Theoretic-Deep-Reinforcement-Learning

Code of Paper "Joint Task Offloading and Resource Optimization in NOMA-based Vehicular Edge Computing: A Game-Theoretic DRL Approach", JSA 2022.

GBLM-Pruner

Are gradient information useful for pruning of LLMs?

GFL

Galaxy Federated Learning Framework （星际联邦学习框架）

GNN-RL-Model-Compression

GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning

graph_nets

PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

Limited-Data-Rolling-Bearing-Fault-Diagnosis-with-Few-shot-Learning

This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning

llm-kick

[ICLR 2024] Jaiswal, A., Gan, Z., Du, X., Zhang, B., Wang, Z., & Yang, Y. Compressing llms: The truth is rarely pure and never simple.

LLM-Pruner

[NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support LLaMA, Llama-2, BLOOM, Vicuna, Baichuan, etc.

LTP-token-pruning

[KDD'22] Learned Token Pruning for Transformers

MTFL-For-Personalised-DNNs

Code for 'Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing', published in IEEE TPDS.

Multi-agent-path-planning

Deep learning model powered by Graph Neural Networks and Reinforcement Learning for Multi-agent path planning at @Inria

Neural-Network-Diffusion

We introduce a novel approach for parameter generation, named neural network diffusion (\textbf{p-diff}, p stands for parameter), which employs a standard latent diffusion model to synthesize a new set of parameters

NIID-Bench

Federated Learning on Non-IID Data Silos: An Experimental Study

PABEE

Code for the paper "BERT Loses Patience: Fast and Robust Inference with Early Exit".

PFL-Non-IID

Personalized federated learning simulation platform with Non-IID and unbalanced dataset

retraining-free-pruning

[NeurIPS 2022] A Fast Post-Training Pruning Framework for Transformers

sparsegpt

Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".

Vehicular-Trajectories-Processing-for-Didi-Open-Data

Vehicular trajectories processing for Didi GAIA Open Data Set

wanda

A simple and effective LLM pruning approach.