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Feng Yang's Projects

a3c icon a3c

Tensorflow implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".

blades icon blades

Blades: A simulator and benchmark for Byzantine-robust federated Learning with Attacks and Defenses Experimental Simulation

cil-ddqn icon cil-ddqn

code of paper 《Independent Reinforcement Learning for Weakly Cooperative Multiagent Traffic Control Problem》

cpo icon cpo

Constrained Policy Optimization

dc3 icon dc3

DC3: A Learning Method for Optimization with Hard Constraints

deepmellow icon deepmellow

Implementation of DeepMellow algorithm (IJCAI 2019)

deeprl_network icon deeprl_network

multi-agent deep reinforcement learning for networked system control.

deeprm icon deeprm

Resource Management with Deep Reinforcement Learning (HotNets '16)

deepslice icon deepslice

DeepSlice: A Deep Learning Approach towards an Efficient and Reliable Network Slicing in 5G Networks

deepslicing icon deepslicing

Source Codes for: DeepSlicing: Deep Reinforcement Learning Assisted Resource Allocation for Network Slicing

drl-code-pytorch icon drl-code-pytorch

Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

drqn-tensorflow icon drqn-tensorflow

Deep recurrent Q Learning using Tensorflow, openai/gym and openai/retro

fedtp icon fedtp

This is official implementation of FedTP (TNNLS.2023) [https://ieeexplore.ieee.org/abstract/document/10130784].

fl-defender icon fl-defender

FL-Defender: Combating Targeted Attacks in Federated Learning

gat icon gat

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

i2q icon i2q

I2Q: A Fully Decentralized Q-Learning Algorithm

icq icon icq

Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS 2021 Spotlight https://arxiv.org/abs/2106.03400)

joint-user-association-and-in-band-backhaul-scheduling-and-in-5g-mmwave-networks icon joint-user-association-and-in-band-backhaul-scheduling-and-in-5g-mmwave-networks

Matlab Simulation for T. K. Vu, M. Bennis, S. Samarakoon, M. Debbah and M. Latva-aho, "Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks," European Wireless 2016; 22th European Wireless Conference, Oulu, Finland, 2016, pp. 1-6. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7499273&isnumber=7499250

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