Results 71 to 80 of about 64,907 (298)

Federated $f$-Differential Privacy

Proceedings of machine learning research, 2021
Federated learning (FL) is a training paradigm where the clients collaboratively learn models by repeatedly sharing information without compromising much on the privacy of their local sensitive data. In this paper, we introduce federated $f$-differential privacy, a new notion specifically tailored to the federated setting, based on the framework of ...
Qinqing Zheng, Shuxiao Chen, Qi Long, Weijie J. Su   +3 more
openaire   +4 more sources

Intelligent Tutoring Systems for Adult Learning in STEM Disciplines

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Intelligent tutoring systems (ITS) are reshaping adult learning in STEM by providing adaptive, data‐driven instruction across classrooms, workplaces, and informal environments. In the context of ITS, this article compares generative AI, which creates personalized explanations and practice materials, with explainable AI, which focuses on ...
Jill Zarestky, Amanda R. Lager Gleason
wiley   +1 more source

Differential Privacy in Practice

Journal of Computing Science and Engineering, 2013
We briefly review the problem of statistical disclosure control under differential privacy model, which entails a formal and ad omnia privacy guarantee separating the utility of the database and the risk due to individual participation. It has born fruitful results over the past ten years, both in theoretical connections to other fields and in ...
Huu HiepNguyen, Kim, J, Yoonho Kim
openaire   +3 more sources

Distribution-invariant differential privacy

Journal of Econometrics, 2023
Differential privacy is becoming one gold standard for protecting the privacy of publicly shared data. It has been widely used in social science, data science, public health, information technology, and the U.S. decennial census. Nevertheless, to guarantee differential privacy, existing methods may unavoidably alter the conclusion of the original data ...
Xuan Bi, Xiaotong Shen
openaire   +4 more sources

Super‐Refractory Status Epilepticus (SRSE) in a Patient With Compound Heterozygous OPA1 Variants: Case Report and Literature Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi, Lara Basovic, Christopher Michael McGraw   +2 more
wiley   +1 more source

Computational Differential Privacy [PDF]

, 2009
The definition of differential privacy has recently emerged as a leading standard of privacy guarantees for algorithms on statistical databases. We offer several relaxations of the definition which require privacy guarantees to hold only against efficient--i.e., computationally-bounded--adversaries.
Ilya Mironov, Omkant Pandey, Omer Reingold, Salil P. Vadhan   +3 more
openaire   +1 more source

The optimal mechanism in differential privacy [PDF]

2014 IEEE International Symposium on Information Theory, 2014
40 pages, 5 figures. Part of this work was presented in DIMACS Workshop on Recent Work on Differential Privacy across Computer Science, October 24 - 26 ...
Quan Geng, Pramod Viswanath
openaire   +2 more sources

Clinical Spectrum and Outcomes of SOX1 Antibody‐Associated Paraneoplastic Neurological Syndromes: A Chinese Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background SOX1 antibody‐positive paraneoplastic neurological syndromes (PNS) exhibit significant population‐specific clinical heterogeneity. While Western cohorts predominantly manifest Lambert‐Eaton myasthenic syndrome (65%–80%), comprehensive clinical characterization and treatment response data in Asian populations remain critically ...
Jin‐Long Ye, Zu‐Ying Kuang, Bo Li, Meng‐Qiu Pan, Li‐Hua Zhou, Yang‐Yang Dai, Si‐Fen Xie, Xian‐Guang Lin, Ye‐Peng Hu, Li‐Hong Jiang, Zhan‐Hang Wang, Wei‐Jing Zhang   +11 more
wiley   +1 more source

Child Health Dataset Publishing and Mining Based on Differential Privacy Preservation

Mathematics
With the emergence and development of application requirements such as data analysis and publishing, it is particularly important to use differential privacy protection technology to provide more reliable, secure, and compliant datasets for research in ...
Wenyu Li, Siqi Wang, Hongwei Wang, Yunlong Lu   +3 more
doaj   +1 more source

MPDP -medoids: Multiple partition differential privacy preserving -medoids clustering for data publishing in the Internet of Medical Things

International Journal of Distributed Sensor Networks, 2021
The tremendous growth of Internet of Medical Things has led to a surge in medical user data, and medical data publishing can provide users with numerous services. However, neglectfully publishing the data may lead to severe leakage of user’s privacy.
Zekun Zhang, Tongtong Wu, Xiaoting Sun, Jiguo Yu   +3 more
doaj   +1 more source