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Astrophysical Properties of the Sirius Binary System Modeled with MESA

Autor: Khan, Momin Y., Castanheria, Barbara G.

Sirius is the brightest star in the night sky and, despite its proximity, this binary system still imposes intriguing questions about its current characteristics and past evolution. Bond et. al. (arXiv:1703.10625) published decades of astrometric mea

Externí odkaz: http://arxiv.org/abs/2411.03267

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HYDRA-FL: Hybrid Knowledge Distillation for Robust and Accurate Federated Learning

Autor: Khan, Momin Ahmad, Chandio, Yasra, Anwar, Fatima Muhammad

Data heterogeneity among Federated Learning (FL) users poses a significant challenge, resulting in reduced global model performance. The community has designed various techniques to tackle this issue, among which Knowledge Distillation (KD)-based tec

Externí odkaz: http://arxiv.org/abs/2409.19912

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A Neurosymbolic Approach to Adaptive Feature Extraction in SLAM

Autor: Chandio, Yasra, Khan, Momin A., Selialia, Khotso, Garcia, Luis, DeGol, Joseph, Anwar, Fatima M.

Publikováno v: 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Autonomous robots, autonomous vehicles, and humans wearing mixed-reality headsets require accurate and reliable tracking services for safety-critical applications in dynamically changing real-world environments. However, the existing tracking approac

Externí odkaz: http://arxiv.org/abs/2407.06889

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Love Tales of Hakim Momin Khan Momin

Autor: Muhammad Tahir Bostan

Publikováno v: Negotiations. 1:20-25

حکیم مومن خان مومن ؔ کے معاشقے This paper aims a comprehensive investigation to identify the various (love stories) of Hakim Momin Khan Momin. Hakim was a romantic poet. His poetry depicts ideal romance. Hakim Momin Khan Momin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0ebfca4c9316f24738eb2776ad592746
https://doi.org/10.54064/negotiations.v1i3.26

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Security Analysis of SplitFed Learning

Autor: Khan, Momin Ahmad, Shejwalkar, Virat, Houmansadr, Amir, Anwar, Fatima Muhammad

Split Learning (SL) and Federated Learning (FL) are two prominent distributed collaborative learning techniques that maintain data privacy by allowing clients to never share their private data with other clients and servers, and fined extensive IoT a

Externí odkaz: http://arxiv.org/abs/2212.01716

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