Results 261 to 270 of about 25,449,411 (299)

The Synthetic Data Vault

2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2016
The goal of this paper is to build a system that automatically creates synthetic data to enable data science endeavors. To achieve this, we present the Synthetic Data Vault (SDV), a system that builds generative models of relational databases. We are able to sample from the model and create synthetic data, hence the name SDV. When implementing the SDV,
Neha Patki, Roy Wedge, Kalyan Veeramachaneni   +2 more
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Synthetic Data

Annual Review of Statistics and Its Application, 2021
Demand for access to data, especially data collected using public funds, is ever growing. At the same time, concerns about the disclosure of the identities of and sensitive information about the respondents providing the data are making the data collectors limit the access to data.
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Synthetic Data: Servicing Privacy

In contemporary society, big tech platforms have leveraged their ownership over global data infrastructures and have established powerful influence over the conditions of digitally mediated life. The ubiquity of platform-mediated information technology has engendered a growing sense of unease about surveillance and loss of personal autonomy.
Munkholm, Johan Lau, Wiehn, Tanja
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Bayesian Generation of Synthetic Data

Generation of synthetic data can be a valuable tool for machine-learning tasks and, in general, managing large volumes of data. This paper presents a technique for creating synthetic data through Bayesian Generation, so that synthetic data maintain the original probability distribution and can be exploited for training Machine-Learning models in place ...
Fosci, Paolo, Nieves, Javier, Psaila, Giuseppe, Bringas, Pablo Garcia   +3 more
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Synthetic Data Generation: Generating High-Utility Synthetic Parcel Data; Applications and Implications of Synthetic Data

2022
As technological advancements occur at an exponential rate, the demand for data also increases. The spread of information through online platforms has also raised concerns about data privacy. To address scarcity and privacy concerns, synthetic data has been gaining popularity and acceptance in various fields.
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A tool for generating synthetic data

Proceedings of the First International Conference on Data Science, E-learning and Information Systems, 2018
It is popular to use real-world data to evaluate data mining techniques. However, there are some disadvantages to use real-world data for such purposes. Firstly, real-world data in most domains is difficult to obtain for several reasons, such as budget, technical or ethical.
Taoxin Peng, Alexander Telle
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Visual Perception with Synthetic Data

2020
In recent years, learning-based methods have become the dominant approach to solving computer vision tasks. A major reason for this development is their automatic adaptation to the particularities of the task at hand by learning a model of the problem from (training) data.
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Taxonomizing Synthetic Data for Law

SSRN Electronic Journal
Synthetic data is increasingly important in data usage and AI design, creating novel legal and policy dilemmas. All too often, discussions of synthetic data treat it as entirely distinct from “real,” collected data, overlooking the risks posed by different kinds and uses of synthetic data.
Cofone, I, Strandburg, KJ, Tilmes, N
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