Home ›
Entities
› academia
› A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data
A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data
Research article (Information Sciences, 2022) · cited 11× · AI/ML
A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data
Summary
A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data is a scholarly article[1].
Key Facts
A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-new-approach-to-data-differential-privacy-based-on-regression-models-under-heteroscedasticity-with-applications-to-mac
MLA“A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-new-approach-to-data-differential-privacy-based-on-regression-models-under-heteroscedasticity-with-applications-to-mac.
BibTeX@misc{4ortxyz_a-new-approach-to-data-differential-privacy-based-on-regression-models-under-heteroscedasticity-with-applications-to-mac_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data}}, year = {2026}, url = {https://4ort.xyz/entity/a-new-approach-to-data-differential-privacy-based-on-regression-models-under-heteroscedasticity-with-applications-to-mac}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A new approach to data differential privacy based on regression models under heteroscedasticity with applications to machine learning repository data — https://4ort.xyz/entity/a-new-approach-to-data-differential-privacy-based-on-regression-models-under-heteroscedasticity-with-applications-to-mac (retrieved 2026-05-24)