5 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.PF2022★ 3 cited
Inference Latency Prediction at the Edge
Zhuojin Li, Marco Paolieri, Leana Golubchik
With the growing workload of inference tasks on mobile devices, state-of-the-art neural architectures (NAs) are typically designed through Neural Architecture Search (NAS) to ident…
cs.LG2020
Backdoor Attacks on Federated Meta-Learning
Chien-Lun Chen, Leana Golubchik, Marco Paolieri
Federated learning allows multiple users to collaboratively train a shared classification model while preserving data privacy. This approach, where model updates are aggregated by…
cs.DC2019★ 5 cited
Throughput Prediction of Asynchronous SGD in TensorFlow
Zhuojin Li, Wumo Yan, Marco Paolieri +1
Modern machine learning frameworks can train neural networks using multiple nodes in parallel, each computing parameter updates with stochastic gradient descent (SGD) and sharing t…