19 citations · 68 across the 18 of their papers we have counts for
3 papers · 1 filter
Auxo: Efficient Federated Learning via Scalable Client Clustering
Jiachen Liu, Fan Lai, Yinwei Dai +3
Federated learning (FL) is an emerging machine learning (ML) paradigm that enables heterogeneous edge devices to collaboratively train ML models without revealing their raw data to…
Accelerating Deep Learning Inference via Learned Caches
Arjun Balasubramanian, Adarsh Kumar, Yuhan Liu +3
Deep Neural Networks (DNNs) are witnessing increased adoption in multiple domains owing to their high accuracy in solving real-world problems. However, this high accuracy has been…
Accelerating Deep Learning Inference via Freezing
Adarsh Kumar, Arjun Balasubramanian, Shivaram Venkataraman +1
Over the last few years, Deep Neural Networks (DNNs) have become ubiquitous owing to their high accuracy on real-world tasks. However, this increase in accuracy comes at the cost o…