Abstract: Nowadays, Federated Learning (FL) has emerged as a prominent technique of model training in Consumer Internet of Things (CIoT) without sharing sensitive local data. Targeting privacy leakage ...

Abstract: Large-scale datacenter networks are increasingly using in-network aggregation (INA) and remote direct memory access (RDMA) techniques to accelerate deep neural network (DNN) training.

Abstract: Federated Learning (FL) is a privacy-preserving distributed Machine Learning (ML) technique. Hierarchical FL is a novel variant of FL applicable to networks with multiple layers. Instead of ...

Abstract: As an ambitious training paradigm, federated learning has garnered increasing attention in recent years, which enables collaborative training of a global model without accessing users’ ...

Abstract: Connected and autonomous vehicles (CAVs) rely heavily upon time-sensitive information update services to ensure the safety of people and assets, and satisfactory entertainment applications.

Abstract: Federated Learning (FL) represents a promising approach to typical privacy concerns associated with centralized Machine Learning (ML) deployments. Despite its well-known advantages, FL is ...

Abstract: Achieving the precise and real-time detection of wheat spikes play a crucial role in wheat growth monitoring for precision agriculture community. Machine-learning methods are commonly ...

Abstract: Projection-aggregation decoding provides state-of-the-art performance for decoding Reed-Muller codes. This type of decoding relies on projecting onto subspaces, decoding the projections, and ...

Abstract: Federated learning has gained significant attention as a privacy-preserving approach for training machine learning models across decentralized devices. However, this distributed learning ...

The Eagles currently lead the NFC East and hold the No. 3 seed in the conference playoff picture. NFL seasons are a marathon, and after losing three straight games, the Eagles (11-5) have won three ...

Abstract: The rapid proliferation of Internet of Things (IoT) devices with sensing, monitoring, and control capabilities has fueled the emergence of diverse real-time IoT applications. These ...

Abstract: Point cloud registration is a fundamental yet challenging task in computer vision and robotics. While framing it as a reconstruction problem has shown promise, traditional reconstruction ...