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FedCPD: Personalized Federated Learning with Prototype-Enhanced ...

https://cis.temple.edu/~jiewu/research/publications/Publication_files/Paper%206190%20Camera%20Ready%20Version.pdf

a major challenge for federated learning in diverse settings. Personalized Federated Learning (PFL), [Tan et al., 2022a] addresses these issues by allowing client-specific models that leverage global insights to enhance local outcomes. The main challenge in PFL lies in balancing global knowledge sharing with preserving client-specific information, making the trade- off an important research ...

Building Classification Models: ID3 and C4.5 - Temple University

https://cis.temple.edu/~ingargio/cis587/readings/id3-c45.html

Introduction ID3 and C4.5 are algorithms introduced by Quinlan for inducing Classification Models, also called Decision Trees, from data.

MAY 2021 - Commencement

https://commencement.temple.edu/sites/commencement/files/TU-Comm-Program-05-07-2021.pdf

I couldn’t be more proud of the diverse and driven students who are graduating this spring. Congratulations to all of you, to your families and to our dedicated faculty and academic advisors who had the pleasure of educating and championing you. If Temple’s founder Russell Conwell were alive to see your collective achievements today, he’d be thrilled and amazed. In 1884, he planted the ...

IDENTITIES BETWEEN HECKE EIGENFORMS

https://cst.temple.edu/sites/cst/files/theses1/bao.pdf

tween Hecke eigenforms, we give another proof that the j-function is algebraic

Prediction of Dental Caries in Pediatric Patients Using Machine ...

https://scholarshare.temple.edu/bitstreams/1c1f1a6d-0f34-4234-8b39-41d9eeb397f0/download

of machine learning (ML) versus a traditional statistical model in predicting dental caries in

A MEANINGFUL FLOOR FOR - Sites

https://sites.temple.edu/ticlj/files/2017/02/30.1.Crootof-TICLJ.pdf

it is grounded in the idea that all weaponry should be subject to ―meaningful human control.‖ This ―intuitively appealing‖ principle is immensely popular,

Balancing Privacy and Accuracy using Significant Gradient Protection in ...

https://cis.temple.edu/~wu/research/publications/Publication_files/J-CT-2024-Balancing%20Privacy%20and%20Accuracy%20using%20Siginificant%20Gradient%20Protection%20in%20Federated%20Learning.pdf

Abstract—Previous state-of-the-art studies have demonstrated that adversaries can access sensitive user data by membership inference attacks (MIAs) in Federated Learning (FL). Intro-ducing differential privacy (DP) into the FL framework is an effective way to enhance the privacy of FL. Nevertheless, in differentially private federated learning (DP-FL), local gradients become excessively ...