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Efficient Online Data Mixing For Language Model Pre-Training
arXiv.org, 2023The data used to pretrain large language models has a decisive impact on a model's downstream performance, which has led to a large body of work on data selection methods that aim to automatically determine the most suitable data to use for pretraining ...
Alon Albalak +3 more
semanticscholar +1 more source
Data Poisoning Attacks and Defenses in Dynamic Crowdsourcing With Online Data Quality Learning
IEEE Transactions on Mobile Computing, 2023Crowdsourcing has found a wide variety of applications, including spectrum sensing, traffic monitoring, as well as data annotation for machine learning based data analytics.
Yuxi Zhao +3 more
semanticscholar +1 more source
Understanding Screen-Reader Users’ Experiences with Online Data Visualizations
International ACM SIGACCESS Conference on Computers and Accessibility, 2021Online data visualizations are widely used to communicate information from simple statistics to complex phenomena, supporting people in gaining important insights from data.
Ather Sharif +3 more
semanticscholar +1 more source
Efficient Online Data-Driven Enhanced-XGBoost Method for Antenna Optimization
IEEE Transactions on Antennas and Propagation, 2022The tremendous progress in artificial intelligence promotes the wide application of machine learning (ML) technology in the field of electronic science.
W. Li, Hao Tang, Can Cui, Y. Hei, X. Shi
semanticscholar +1 more source
Online Data Valuation and Pricing for Machine Learning Tasks in Mobile Health
IEEE Conference on Computer Communications, 2022Mobile health (mHealth) applications, benefiting from mobile computing, have emerged rapidly in recent years, and generated a large volume of mHealth data. However, these valuable data are dispersed across isolated devices or organizations, which hinders
Anran Xu +3 more
semanticscholar +1 more source
ESA-Stream: Efficient Self-Adaptive Online Data Stream Clustering
IEEE Transactions on Knowledge and Data Engineering, 2022Many big data applications produce a massive amount of high-dimensional, real-time, and evolving streaming data. Clustering such data streams with both effectiveness and efficiency are critical for these applications.
Yanni Li +5 more
semanticscholar +1 more source
Revisiting Online Data Markets in 2022
SIGMOD record, 2022Well-functioning data markets match sellers with buyers to allocate data effectively. Although most of today's data markets fall short of this ideal, there is a renewed interest in online data marketplaces that may fulfill the promise of data markets. In
J. Kennedy +3 more
semanticscholar +1 more source
Coupled Atmosphere–Ocean Reconstruction of the Last Millennium Using Online Data Assimilation
Paleoceanography and Paleoclimatology, 2021We use online data assimilation to combine information from a linear inverse model of coupled atmosphere‐ocean dynamics with proxy records to create a new annual‐resolution reconstruction of atmosphere and ocean fields over the last millennium ...
W. Perkins, G. Hakim
semanticscholar +1 more source
Proceedings of the VLDB Endowment, 2011
The Web contains a significant volume of structured data in various domains, but a lot of data are dirty and erroneous, and they can be propagated through copying. While data integration techniques allow querying structured data on the Web, they take the union of the answers retrieved from different sources and can thus return conflicting information ...
Liu, X. +3 more
openaire +1 more source
The Web contains a significant volume of structured data in various domains, but a lot of data are dirty and erroneous, and they can be propagated through copying. While data integration techniques allow querying structured data on the Web, they take the union of the answers retrieved from different sources and can thus return conflicting information ...
Liu, X. +3 more
openaire +1 more source