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Mitigating covariate shift in non-colocated data with learned parameter priors

Autor: Khan, Behraj, Mirza, Behroz, Durrani, Nouman, Syed, Tahir

When training data are distributed across{ time or space,} covariate shift across fragments of training data biases cross-validation, compromising model selection and assessment. We present \textit{Fragmentation-Induced covariate-shift Remediation} (

Externí odkaz: http://arxiv.org/abs/2411.06499

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Textual analysis of End User License Agreement for red-flagging potentially malicious software

Autor: Khan, Behraj, Syed, Tahir, Khan, Zeshan, Rafi, Muhammad

New software and updates are downloaded by end users every day. Each dowloaded software has associated with it an End Users License Agreements (EULA), but this is rarely read. An EULA includes information to avoid legal repercussions. However,this pr

Externí odkaz: http://arxiv.org/abs/2403.09715

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Dynamic Model Switching for Improved Accuracy in Machine Learning

Autor: Hasani, Syed Tahir Abbas

In the dynamic landscape of machine learning, where datasets vary widely in size and complexity, selecting the most effective model poses a significant challenge. Rather than fixating on a single model, our research propels the field forward with a n

Externí odkaz: http://arxiv.org/abs/2404.18932

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Akademický článek

Investigating the impacts of different degrees of deficit irrigation and nitrogen interactions on assimilate translocation, yield, and resource use efficiencies in winter wheat

Autor: Tingxuan Zhuang, Syed Tahir Ata-UI-Karim, Ben Zhao, Xiaojun Liu, Yongchao Tian, Yan Zhu, Weixing Cao, Qiang Cao

Publikováno v: Agricultural Water Management, Vol 304, Iss , Pp 109089- (2024)

Water and nitrogen (N) are recognized as the primary determinants influencing the development and output of winter wheat. They affect the growth of winter wheat not only through their own changes, but also through their interaction. The translocation

Externí odkaz: https://doaj.org/article/260c35d11ab449b68d491d91d8980aa6

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