Sixing Yu

J. Pablo Muñoz

CoRR, 2023

Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models.

[BibT_eX]

[DOI]

J. Pablo Muñoz

CoRR, 2023

Enhancing Heterogeneous Federated Learning with Knowledge Extraction and Multi-Model Fusion.

[BibT_eX]

[DOI]

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Heterogeneous Federated Learning using Dynamic Model Pruning and Adaptive Gradient.

[BibT_eX]

[DOI]

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2022

Towards Seamless Management of AI Models in High-Performance Computing.

[BibT_eX]

[DOI]

Tristan Vanderbruggen

Xipeng Shen

CoRR, 2022

Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2022

Resource-aware Federated Learning using Knowledge Extraction and Multi-model Fusion.

[BibT_eX]

[DOI]

Wei Qian

CoRR, 2022

SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Adaptive Dynamic Pruning for Non-IID Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2021

GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Auto Graph Encoder-Decoder for Neural Network Pruning.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Auto Graph Encoder-Decoder for Model Compression and Network Acceleration.

[BibT_eX]

[DOI]