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of 4
pro vyhledávání: '"Bai, Jiamu"'
Federated Learning (FL) has recently been applied to the parameter-efficient fine-tuning of Large Language Models (LLMs). While promising, it raises significant challenges due to the heterogeneous resources and data distributions of clients. This stu
Externí odkaz:
http://arxiv.org/abs/2402.11505
Multiple robots could perceive a scene (e.g., detect objects) collaboratively better than individuals, although easily suffer from adversarial attacks when using deep learning. This could be addressed by the adversarial defense, but its training requ
Externí odkaz:
http://arxiv.org/abs/2303.09495
Autor:
Samsonau, Sergey V, Kurbonova, Aziza, Jiang, Lu, Lashen, Hazem, Bai, Jiamu, Merchant, Theresa, Wang, Ruoxi, Mehnaz, Laiba, Wang, Zecheng, Patil, Ishita
We report a framework that enables the wide adoption of authentic research educational methodology at various schools by addressing common barriers. The guiding principles we present were applied to implement a program in which teams of students with
Externí odkaz:
http://arxiv.org/abs/2210.08966
Autor:
Samsonau, Sergey V, Kurbonova, Aziza, Jiang, Lu, Lashen, Hazem, Bai, Jiamu, Merchant, Theresa, Wang, Ruoxi, Mehnaz, Laiba, Wang, Zecheng, Patil, Ishita
We report a methodology in which students gain experience in authentic research by developing artificial intelligence (AI) solutions for researchers in natural sciences. While creating education benefits for students, our approach also directly benef
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9560880c46b58686c1089c4c97bbcfb3
http://arxiv.org/abs/2210.08966
http://arxiv.org/abs/2210.08966