yusx-swapp / GNN-RL-Model-Compression
GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning
☆54Updated last year
Related projects: ⓘ
- Link Scheduling using Graph Neural Networks, IEEE TWC☆30Updated 6 months ago
- ☆86Updated last year
- [IEEE Access] "Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-constrained Edge Computing Systems" and […☆32Updated last year
- Reference code for https://arxiv.org/abs/1906.08879☆16Updated 4 years ago
- Self-Supervised Deep Learning based Surrogate Models for Fault-Tolerant Edge Computing☆19Updated last year
- Implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs".☆93Updated last year
- PipeEdge: Pipeline Parallelism for Large-Scale Model Inference on Heterogeneous Edge Devices☆25Updated 7 months ago
- This project will realize experiments about BranchyNet partitioning using pytorch framework☆28Updated 4 years ago
- ☆34Updated last year
- FedFormer: Contextual Federation with Attention in Reinforcement Learning (AAMAS 2023)☆38Updated 11 months ago
- ☆11Updated 4 years ago
- Code Implemntion from the article Multi-Armed Bandit Based Client Schedulingfor Federated Learning☆16Updated 3 years ago
- Using Feature Decomposition method to accelerate GNN inference☆12Updated 2 years ago
- Deep reinforcement learning for REsource Allocation in streaM processing☆26Updated last year
- ☆20Updated last year
- https://arxiv.org/abs/1706.04972☆41Updated 5 years ago
- PyTorch implementation of the paper: Multi-Agent Collaborative Inference via DNN Decoupling: Intermediate Feature Compression and Edge Le…☆25Updated 10 months ago
- Code for paper "Real-time Neural Network Inference on Extremely Weak Devices: Agile Offloading with Explainable AI" (MobiCom'22)☆15Updated last year
- FedNAS: Federated Deep Learning via Neural Architecture Search☆50Updated 3 years ago
- This open source library is available to summarize several years of research papers on graph reinforcement learning for the convenience o…☆17Updated 2 years ago
- 2-stage pruning to favor distributed inference (local device compute half of the model, upload the feature for further computing on stron…☆23Updated 6 years ago
- Implementation of "Federated Control with Hierarchical Multi-Agent Deep Reinforcement Learning" (https://arxiv.org/pdf/1712.08266.pdf)☆36Updated 6 years ago
- Hao Jin, Yang Peng, Wenhao Yang, Shusen Wang and Zhihua Zhang. Federated Reinforcement Learning with Environment Heterogeneity. AISTATS, …☆53Updated 2 years ago
- ☆23Updated 2 years ago
- vector quantization for stochastic gradient descent.☆33Updated 4 years ago
- The code of paper Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. Zhihai Wang, Xijun Li,…☆46Updated last year
- Federated learning is a distributed learning method that trains a deep network on user devices without collecting data from central serve…☆12Updated 4 years ago
- Distributed deep learning cluster simulation environment and RL-GNN resource management implementations.☆11Updated last year
- Publication catalog for research on Federated RL (FRL).☆76Updated 3 years ago
- HEFT, randomHEFT and IPEFT algorithms for static list DAG Scheduling☆46Updated 4 years ago