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Business Information ReviewThe rise of data-driven businesses poses a number of significant challenges for contemporary organisations. These include legal and ethical considerations arising from the use of personal data, the growing challenges of information security, and the difficulty managing the volume of data generated in business transactions of different kinds.
Jimmy Nassif, Joe Tekli, Marc Kamradt
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CoRR, 2023 This study leverages synthetic data as a validation set to reduce overfitting and ease the selection of the best model in AI development. While synthetic data have been used for augmenting the training set, we find that synthetic data can also significantly diversify the validation set, offering marked advantages in domains like healthcare, where data ...
Qixin Hu, Alan L. Yuille, Zongwei Zhou
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CoRR, 2023 Synthetic data are becoming a critical tool for building artificially intelligent systems. Simulators provide a way of generating data systematically and at scale. These data can then be used either exclusively, or in conjunction with real data, for training and testing systems. Synthetic data are particularly attractive in cases where the availability
Daniel McDuff +2 more
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Synthetic Data for Model Selection
CoRR, 2021 Recent breakthroughs in synthetic data generation approaches made it possible to produce highly photorealistic images which are hardly distinguishable from real ones. Furthermore, synthetic generation pipelines have the potential to generate an unlimited number of images.
Matan Fintz +4 more
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Synthetic data, real errors: how (not) to publish and use synthetic data
CoRR, 2023 Proceedings of the 40th International Conference on Machine Learning (ICML 2023)
Boris van Breugel +2 more
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Synthetic data for reef modelling
Ecological Informatics, 2023 Synthetic data mimics the statistical properties of real-world datasets while removing reference to sensitive or confidential information in the original dataset (Quintana, 2020). Synthetic data is also useful for general model testing and development, with many methods available for generating data from machine learning models (Raghunathan, 2021 ...
Rose Crocker +4 more
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Likelihood-Based Finite Sample Inference for Synthetic Data from Pareto Model
Revstat Statistical Journal, 2023 Statistical agencies often publish microdata or synthetic data to protect confidentiality of survey respondents. This is more prevalent in case of income data.
Nutan Mishra , Sandip Barui
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Unsupervised Cyclic Siamese Networks Automating Cell Imagery Analysis
Algorithms, 2023 Novel neural network models that can handle complex tasks with fewer examples than before are being developed for a wide range of applications. In some fields, even the creation of a few labels is a laborious task and impractical, especially for data ...
Dominik Stallmann, Barbara Hammer
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CoRR, 2019 Discussion paper at FATES on the Web ...
Luke Rodriguez, Bill Howe
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The Journal of Privacy and Confidentiality, 2020 Enhancing microdata access is one of the strategic priorities for the Australian Bureau of Statistics (ABS) in its transformation program. However, balancing the trade-off between enhancing data access and protecting confidentiality is a delicate act ...
Chien-Hung Chien +2 more
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