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Low Rank Transform Domain Adaptive Filtering
1997This paper introduces a least squares, matrix based framework for adaptive filtering that includes Normalized LMS, Affine Projection, and Recursive Least Squares as special cases. We then introduce other transform domain based methods and show how to create optimal low rank versions. We also discuss efficient implementation of our method.
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A concise analysis of low-rank adaptation
Applied and Computational EngineeringRecent years the pre-trained language models have been proved to be a transformative technology within the domain of Natural Language Processing (NLP). From early word embeddings to modern transformer-based architectures, the success of models like BERT, GPT-3, and their variants has led to remarkable advancements in various NLP tasks.
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RANK links thymic regulatory T cells to fetal loss and gestational diabetes in pregnancy
Nature, 2020Magdalena Paolino +2 more
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Recent developments in drying and dewatering for low rank coals
Progress in Energy and Combustion Science, 2015Zhonghao Rao, Cong-Liang Huang
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Roles of the RANKL–RANK axis in antitumour immunity — implications for therapy
Nature Reviews Clinical Oncology, 2018Mark J Smyth +2 more
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Low-Rank Modeling and Its Applications in Image Analysis
ACM Computing Surveys, 2015Can YANG, Weichuan Yu
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Dysregulated Osteoprotegerin/RANK Ligand/RANK Axis in Clinical and Experimental Heart Failure
Circulation, 2005Thor Ueland +2 more
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