ystex

FedHSSL

The implementation of FedHSSL algorithm published in the paper "A Hybrid Self-Supervised Learning Framework for Vertical Federated Learning".

CreamFL

[ICLR 2023] Multimodal Federated Learning via Contrastive Representation Ensemble

fed-multimodal

[KDD 2023] FedMultimodal

FederatedGPT-Shepherd

Shepherd: A foundational framework enabling federated instruction tuning for large language models

OpenFedLLM

nanoGPT-LoRA

The simplest, fastest repository for training/finetuning medium-sized GPTs with LoRA support.

LLM

该仓库主要记录 大模型（LLMs） 算法工程师相关的面试题与我写的答案

llm_interview_note

主要记录大语言大模型（LLMs） 算法（应用）工程师相关的知识及面试题

Conference-Accepted-Paper-List

Some Conferences' accepted paper lists (including AI, ML, Robotic)

TDCD

Code for Tiered Decentralized Coordinate Descent (TDCD)

latbin

Python package for quantizing data onto a multi-dimensional lattice

RSS-field-stimation

This code is focused on the application of a certain ML algorithms in a specific scenario in order to estimate the received signal strength (RSS) at differents point in that scenario, from the information provided by low-cost sensors whose measurements have a very low precise. The selected ML algorithm is Gaussian Processes for Regression (GPR) and the code is implemented in Python. The theoretical background is based on the following project: "Recursive Estimation of Dynamic RSS Fields Based of Crowdsourcing and Gaussiand Processes" which authors are: Irene Santos, Juan José Murillo-Fuentes and Petar M. Djuric.

onn

Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)

FTRL-pytorch

Implementation of FTRL (Follow the Regularized Leader)

PyTorch-Weight-Pruning

A PyTorch implementation of "Learning both Weights and Connections for Efficient Neural Networks", Song Han et al. 2015.

deep-compression

Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626

HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients

[ICLR 2021] HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

pytorch-network-slimming

A package to make do Network Slimming a little easier

Synaptic-Flow

Sub-FedAvg

Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity

implementation-of-pruning-filters

A reproduction of PRUNING FILTERS FOR EFFICIENT CONVNETS

PruningFilters

Pruning Filters For Efficient ConvNets, PyTorch Implementation.

Pruning_filters_for_efficient_convnets

PyTorch implementation of "Pruning Filters For Efficient ConvNets"

filter-pruning-geometric-median

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)

Torch-Pruning

[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs

PruneFL

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

Deep-Learning-Interview-Book

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

Machine-Learning-Interview-Prep

flex-vfl

Code for running and evaluating Flexible Vertical Federated Learning (Flex-VFL)