Pervasive AI for IoT applications: A survey on resource-efficient distributed artificial intelligence
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of
Things (IoT) applications and services, spanning from recommendation systems and speech …
Things (IoT) applications and services, spanning from recommendation systems and speech …
Distributed graph neural network training: A survey
Graph neural networks (GNNs) are a type of deep learning models that are trained on
graphs and have been successfully applied in various domains. Despite the effectiveness of …
graphs and have been successfully applied in various domains. Despite the effectiveness of …
Unleashing the tiger: Inference attacks on split learning
We investigate the security of split learning---a novel collaborative machine learning
framework that enables peak performance by requiring minimal resource consumption. In …
framework that enables peak performance by requiring minimal resource consumption. In …
Randomness in neural network training: Characterizing the impact of tooling
The quest for determinism in machine learning has disproportionately focused on
characterizing the impact of noise introduced by algorithmic design choices. In this work, we …
characterizing the impact of noise introduced by algorithmic design choices. In this work, we …
Merlin hugeCTR: GPU-accelerated recommender system training and inference
Z Wang, Y Wei, M Lee, M Langer, F Yu, J Liu… - Proceedings of the 16th …, 2022 - dl.acm.org
In this talk, we introduce Merlin HugeCTR. Merlin HugeCTR is an open source, GPU-
accelerated integration framework for click-through rate estimation. It optimizes both training …
accelerated integration framework for click-through rate estimation. It optimizes both training …
Distributed network intrusion detection system in satellite-terrestrial integrated networks using federated learning
The existing satellite-terrestrial integrated networks (STINs) suffer from security and privacy
concerns due to the limited resources, poor attack resistance and high privacy requirements …
concerns due to the limited resources, poor attack resistance and high privacy requirements …
Imtidad: a reference architecture and a case study on developing distributed AI services for skin disease diagnosis over cloud, fog and edge
Several factors are motivating the development of preventive, personalized, connected,
virtual, and ubiquitous healthcare services. These factors include declining public health …
virtual, and ubiquitous healthcare services. These factors include declining public health …
Federated learning and next generation wireless communications: A survey on bidirectional relationship
In order to meet the extremely heterogeneous requirements of the next generation wireless
communication networks, research community is increasingly dependent on using machine …
communication networks, research community is increasingly dependent on using machine …
From distributed machine to distributed deep learning: a comprehensive survey
M Dehghani, Z Yazdanparast - Journal of Big Data, 2023 - Springer
Artificial intelligence has made remarkable progress in handling complex tasks, thanks to
advances in hardware acceleration and machine learning algorithms. However, to acquire …
advances in hardware acceleration and machine learning algorithms. However, to acquire …
A survey on auto-parallelism of large-scale deep learning training
P Liang, Y Tang, X Zhang, Y Bai, T Su… - … on Parallel and …, 2023 - ieeexplore.ieee.org
Deep learning (DL) has gained great success in recent years, leading to state-of-the-art
performance in research community and industrial fields like computer vision and natural …
performance in research community and industrial fields like computer vision and natural …