1 citations · 2 across the 3 of their papers we have counts for
3 papers
Equitable-FL: Federated Learning with Sparsity for Resource-Constrained Environment
Indrajeet Kumar Sinha, Shekhar Verma, Krishna Pratap Singh
In Federated Learning, model training is performed across multiple computing devices, where only parameters are shared with a common central server without exchanging their data in…
FAM: fast adaptive federated meta-learning
Indrajeet Kumar Sinha, Shekhar Verma, Krishna Pratap Singh
In this work, we propose a fast adaptive federated meta-learning (FAM) framework for collaboratively learning a single global model, which can then be personalized locally on indiv…
Learning to Learn with Indispensable Connections
Sambhavi Tiwari, Manas Gogoi, Shekhar Verma +1
Meta-learning aims to solve unseen tasks with few labelled instances. Nevertheless, despite its effectiveness for quick learning in existing optimization-based methods, it has seve…