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05/19/2023
Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models
Foundation Models (FMs), such as BERT, GPT, ViT, and CLIP, have demonstr...
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12/13/2022
Towards Seamless Management of AI Models in High-Performance Computing
With the increasing prevalence of artificial intelligence (AI) in divers...
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11/09/2022
Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search
Federated Learning (FL) is extensively used to train AI/ML models in dis...
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08/16/2022
Resource-aware Federated Learning using Knowledge Extraction and Multi-model Fusion
With increasing concern about user data privacy, federated learning (FL)...
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11/29/2021
SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning
Efficient federated learning is one of the key challenges for training a...
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06/13/2021
Adaptive Dynamic Pruning for Non-IID Federated Learning
Federated Learning (FL) has emerged as a new paradigm of training machin...
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02/05/2021
GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning
Model compression is an essential technique for deploying deep neural ne...
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11/25/2020
