Zobrazeno 1 - 10
of 191
pro vyhledávání: '"He, Shiqi"'
In Federated Learning (FL), common privacy-enhancing techniques, such as secure aggregation and distributed differential privacy, rely on the critical assumption of an honest majority among participants to withstand various attacks. In practice, howe
Externí odkaz:
http://arxiv.org/abs/2401.02880
Autor:
Ramamonjison, Rindranirina, Yu, Timothy T., Li, Raymond, Li, Haley, Carenini, Giuseppe, Ghaddar, Bissan, He, Shiqi, Mostajabdaveh, Mahdi, Banitalebi-Dehkordi, Amin, Zhou, Zirui, Zhang, Yong
The Natural Language for Optimization (NL4Opt) Competition was created to investigate methods of extracting the meaning and formulation of an optimization problem based on its text description. Specifically, the goal of the competition is to increase
Externí odkaz:
http://arxiv.org/abs/2303.08233
Federated learning (FL) is an effective technique to directly involve edge devices in machine learning training while preserving client privacy. However, the substantial communication overhead of FL makes training challenging when edge devices have l
Externí odkaz:
http://arxiv.org/abs/2212.01523
Autor:
Ramamonjison, Rindranirina, Li, Haley, Yu, Timothy T., He, Shiqi, Rengan, Vishnu, Banitalebi-Dehkordi, Amin, Zhou, Zirui, Zhang, Yong
We describe an augmented intelligence system for simplifying and enhancing the modeling experience for operations research. Using this system, the user receives a suggested formulation of an optimization problem based on its description. To facilitat
Externí odkaz:
http://arxiv.org/abs/2209.15565
Compared with full client participation, partial client participation is a more practical scenario in federated learning, but it may amplify some challenges in federated learning, such as data heterogeneity. The lack of inactive clients' updates in p
Externí odkaz:
http://arxiv.org/abs/2206.05891
Traditional one-bit compressed stochastic gradient descent can not be directly employed in multi-hop all-reduce, a widely adopted distributed training paradigm in network-intensive high-performance computing systems such as public clouds. According t
Externí odkaz:
http://arxiv.org/abs/2204.06787
Publikováno v:
In European Polymer Journal 7 August 2024 216
Autor:
Liu, Wanshun, Zhao, Mouming, Gan, Lishe, Sun, Baoguo, He, Shiqi, Liu, Yang, Liu, Lei, Li, Wu, Chen, Jing, Zhang, Jianan, Xu, Jucai
Publikováno v:
In Food Chemistry: X 30 June 2024 22
Autor:
Chen, Nuo, Zhang, Boqing, Yang, Haofan, Lu, Xinda, He, Shiqi, Hu, Yuhang, Chen, Yuntian, Zhang, Xinliang, Xu, Jing
We raise a detuning-dependent loss mechanism to describe the soliton formation dynamics when the lumped filtering operation is manipulated in anomalous group velocity dispersion regime, using stability analysis of generalized Lugiato-Lefever equation
Externí odkaz:
http://arxiv.org/abs/2107.12686
Communication is a crucial phase in the context of distributed training. Because parameter server (PS) frequently experiences network congestion, recent studies have found that training paradigms without a centralized server outperform the traditiona
Externí odkaz:
http://arxiv.org/abs/2004.09125