Zobrazeno 1 - 10
of 335
pro vyhledávání: '"Ji Mingyue"'
Secure aggregation is concerned with the task of securely uploading the inputs of multiple users to an aggregation server without letting the server know the inputs beyond their summation. It finds broad applications in distributed machine learning p
Externí odkaz:
http://arxiv.org/abs/2410.14035
Autor:
McManus, Maxwell, Rinchen, Tenzin, Dey, Annoy, Thota, Sumanth, Zhang, Zhaoxi, Hu, Jiangqi, Wang, Xi, Ji, Mingyue, Mastronarde, Nicholas, Bentley, Elizabeth Serena, Medley, Michael, Guan, Zhangyu
In this work, we present a new federation framework for UnionLabs, an innovative cloud-based resource-sharing infrastructure designed for next-generation (NextG) and Internet of Things (IoT) over-the-air (OTA) experiments. The framework aims to reduc
Externí odkaz:
http://arxiv.org/abs/2408.14460
In federated learning (FL), data heterogeneity is the main reason that existing theoretical analyses are pessimistic about the convergence rate. In particular, for many FL algorithms, the convergence rate grows dramatically when the number of local u
Externí odkaz:
http://arxiv.org/abs/2407.15567
Elasticity plays an important role in modern cloud computing systems. Elastic computing allows virtual machines (i.e., computing nodes) to be preempted when high-priority jobs arise, and also allows new virtual machines to participate in the computat
Externí odkaz:
http://arxiv.org/abs/2403.00585
Autor:
Wang, Xi, Hatasaka, Bryan, Liu, Zhengyan, Tope, Sayali, Karkhanis, Mohit, Noh, Seungbeom, Sium, Farhan, Mural, Ravi V., Kim, Hanseup, Mastrangelo, Carlos, Zang, Ling, Schnable, James, Ji, Mingyue
With the rapid development of cloud and edge computing, Internet of Things (IoT) applications have been deployed in various aspects of human life. In this paper, we design and implement a holistic LoRa-based IoT system with LoRa communication capabil
Externí odkaz:
http://arxiv.org/abs/2401.13569
In 2018, Yang et al. introduced a novel and effective approach, using maximum distance separable (MDS) codes, to mitigate the impact of elasticity in cloud computing systems. This approach is referred to as coded elastic computing. Some limitations o
Externí odkaz:
http://arxiv.org/abs/2401.12151
Connected and automated vehicles (CAVs) have become a transformative technology that can change our daily life. Currently, millimeter-wave (mmWave) bands are identified as the promising CAV connectivity solution. While it can provide high data rate,
Externí odkaz:
http://arxiv.org/abs/2401.01822
Channel modeling is fundamental in advancing wireless systems and has thus attracted considerable research focus. Recent trends have seen a growing reliance on data-driven techniques to facilitate the modeling process and yield accurate channel predi
Externí odkaz:
http://arxiv.org/abs/2401.01288
This paper considers the secure aggregation problem for federated learning under an information theoretic cryptographic formulation, where distributed training nodes (referred to as users) train models based on their own local data and a curious-but-
Externí odkaz:
http://arxiv.org/abs/2310.09889
Autor:
Wang, Shiqiang, Ji, Mingyue
In federated learning (FL), clients usually have diverse participation statistics that are unknown a priori, which can significantly harm the performance of FL if not handled properly. Existing works aiming at addressing this problem are usually base
Externí odkaz:
http://arxiv.org/abs/2306.03401