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cagrad

fedml

A Research-oriented Federated Learning Library. Supporting distributed computing, mobile/IoT on-device training, and standalone simulation. Best Paper Award at NeurIPS 2020 Federated Learning workshop. Join our Slack Community:(https://join.slack.com/t/fedml/shared_invite/zt-havwx1ee-a1xfOUrATNfc9DFqU~r34w)

heshandevaka.github.io

minimalrl

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

mlsys2022-flworkshop

moco

This repository contains the codebase used to generate the main results of "Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach, which has been accepted to ICLR 2023."

moco-plus

Code for implementing MoCo+ (ICASSP 2024)

pareto-hypernetworks

Official implementation of Learning The Pareto Front With HyperNetworks [ICLR 2021]

pcgrad

Code for "Gradient Surgery for Multi-Task Learning"

rl-adventure

Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

rl-adventure-2

PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay

template

trade-off-mol

Experiments on trade-off among optimization, generalization and conflict aversion in multi-objective learning (MOL), and introducing MoDo.