zengzh (southamptonzeng)

southamptonzeng

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Company:University of Electronic Science and Technology of China

Location:Chengdu, Sichuan, China

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zengzh's starred repositories

Fed-QSSL

This repository contains the code for the paper: Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity.

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CreamFL

[ICLR 2023] Multimodal Federated Learning via Contrastive Representation Ensemble

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All-In-One-Neural-Composition

PyTorch code for our paper "Resource-Adaptive Federated Learning with All-In-One Neural Composition" (NeurIPS2022)

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snntorch

Deep and online learning with spiking neural networks in Python

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personalized-collaborative-llms

Exploration on-device self-supervised collaborative fine-tuning of large language models with limited local data availability, using Low-Rank Adaptation (LoRA). We introduce three distinct trust-weighted gradient aggregation schemes: weight similarity-based, prediction similarity-based and validation performance-based.

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QuaRot

Code for QuaRot, an end-to-end 4-bit inference of large language models.

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FedAgg

[INFOCOM 2024] Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration

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Curious-Black-Cat

纪念我的老朋友

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MIT-6.5940

All Homeworks for TinyML and Efficient Deep Learning Computing 6.5940 • Fall • 2023 • https://efficientml.ai

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HtFLlib

Configure one file for model heterogeneity. Consistent GPU memory usage for single or multiple clients.

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Dynamic_Model_Pruning_with_Feedback

Implement of Dynamic Model Pruning with Feedback with pytorch

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PruneFL

This is the code repository for the following paper: "Model pruning enables efficient federated learning on edge devices".

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clash-for-linux-backup

基于Clash Core 制作的Clash For Linux备份仓库 A Clash For Linux Backup Warehouse Based on Clash Core

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scale-fl

Code for ScaleFL

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Awesome-FL

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

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HFL_Survey

Heterogeneous Federated Learning: State-of-the-art and Research Challenges

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AugHFL

Robust Heterogeneous Federated Learning under Data Corruption

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FedProto

[AAAI'22] FedProto: Federated Prototype Learning across Heterogeneous Clients

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FATE-LLM

Federated Learning for LLMs.

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WeChatOrderSystem

微信点餐系统-SpringBoot开发

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bluefog

Distributed and decentralized training framework for PyTorch over graph

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