Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Mohapatra, Shubhankar"'
Publikováno v:
PVLDB Volume 17, 2024
Despite several works that succeed in generating synthetic data with differential privacy (DP) guarantees, they are inadequate for generating high-quality synthetic data when the input data has missing values. In this work, we formalize the problems
Externí odkaz:
http://arxiv.org/abs/2310.11548
Hyperparameter optimization is a ubiquitous challenge in machine learning, and the performance of a trained model depends crucially upon their effective selection. While a rich set of tools exist for this purpose, there are currently no practical hyp
Externí odkaz:
http://arxiv.org/abs/2111.04906
Organizations are increasingly relying on data to support decisions. When data contains private and sensitive information, the data owner often desires to publish a synthetic database instance that is similarly useful as the true data, while ensuring
Externí odkaz:
http://arxiv.org/abs/2012.15713
Cryptocurrencies, such as Bitcoin, are becoming increasingly popular, having been widely used as an exchange medium in areas such as financial transaction and asset transfer verification. However, there has been a lack of solutions that can support r
Externí odkaz:
http://arxiv.org/abs/2003.04967
Publikováno v:
Springer Lecture Notes in Networks and Systems 2016 - 2020
Microarray data analysis is one of the major area of research in the field computational biology. Numerous techniques like clustering, biclustering are often applied to microarray data to extract meaningful outcomes which play key roles in practical
Externí odkaz:
http://arxiv.org/abs/1909.00237
Akademický článek
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Akademický článek
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Publikováno v:
Studies in Health Technology & Informatics; 2021, Issue 281, p193-197, 5p, 2 Diagrams, 1 Chart, 1 Graph
