4 citations · 4 across the 4 of their papers we have counts for
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PruneFuse: Efficient Data Selection via Weight Pruning and Network Fusion
Humaira Kousar, Hasnain Irshad Bhatti, Jaekyun Moon
Efficient data selection is crucial for enhancing the training efficiency of deep neural networks and minimizing annotation requirements. Traditional methods often face high comput…
Pruning-based Data Selection and Network Fusion for Efficient Deep Learning
Humaira Kousar, Hasnain Irshad Bhatti, Jaekyun Moon
Efficient data selection is essential for improving the training efficiency of deep neural networks and reducing the associated annotation costs. However, traditional methods tend…
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
Mohammad Mahdi Rahimi, Hasnain Irshad Bhatti, Younghyun Park +2
Federated Learning (FL) is a decentralized machine learning paradigm that enables collaborative model training across dispersed nodes without having to force individual nodes to sh…
Locally Supervised Learning with Periodic Global Guidance
Hasnain Irshad Bhatti, Jaekyun Moon
Locally supervised learning aims to train a neural network based on a local estimation of the global loss function at each decoupled module of the network. Auxiliary networks are t…