Zobrazeno 1 - 10
of 4 231
pro vyhledávání: '"model reuse"'
The ubiquity of large-scale Pre-Trained Models (PTMs) is on the rise, sparking interest in model hubs, and dedicated platforms for hosting PTMs. Despite this trend, a comprehensive exploration of the challenges that users encounter and how the commun
Externí odkaz:
http://arxiv.org/abs/2401.13177
The rapid expansion of foundation pre-trained models and their fine-tuned counterparts has significantly contributed to the advancement of machine learning. Leveraging pre-trained models to extract knowledge and expedite learning in real-world tasks,
Externí odkaz:
http://arxiv.org/abs/2308.09158
This paper studies multiparty learning, aiming to learn a model using the private data of different participants. Model reuse is a promising solution for multiparty learning, assuming that a local model has been trained for each party. Considering th
Externí odkaz:
http://arxiv.org/abs/2305.13871
Due to the dynamics of wireless environment and limited bandwidth, wireless federated learning (FL) is challenged by frequent transmission errors and incomplete aggregation from devices. In order to overcome these challenges, we propose a global mode
Externí odkaz:
http://arxiv.org/abs/2306.05380
Autor:
Jiang, Wenxin, Synovic, Nicholas, Hyatt, Matt, Schorlemmer, Taylor R., Sethi, Rohan, Lu, Yung-Hsiang, Thiruvathukal, George K., Davis, James C.
Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art architectures grow more complex. Following the path of traditional softw
Externí odkaz:
http://arxiv.org/abs/2303.02552
Interface-Based Search and Automatic Reassembly of CAD Models for Database Expansion and Model Reuse
Publikováno v:
In Computer-Aided Design February 2024 167
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
LI Xinchun, ZHAN Dechuan
Publikováno v:
Jisuanji kexue yu tansuo, Vol 16, Iss 10, Pp 2310-2319 (2022)
Traditional machine learning always takes a data centralized training strategy, while the transmission cost or data privacy protection in many real-world applications results in distributed and isolated data. Distributed learning provides an effectiv
Externí odkaz:
https://doaj.org/article/65809856c6114549b2cf72226f1aa55d
Autor:
Ali, Ahsan, Sharma, Hemant, Kettimuthu, Rajkumar, Kenesei, Peter, Trujillo, Dennis, Miceli, Antonino, Foster, Ian, Coffee, Ryan, Thayer, Jana, Liu, Zhengchun
Publikováno v:
2022 IEEE International Conference on Cluster Computing (CLUSTER)
Extracting actionable information rapidly from data produced by instruments such as the Linac Coherent Light Source (LCLS-II) and Advanced Photon Source Upgrade (APS-U) is becoming ever more challenging due to high (up to TB/s) data rates. Convention
Externí odkaz:
http://arxiv.org/abs/2204.09805