Results 41 to 50 of about 1,916,192 (291)

Concentrated Differential Privacy

CoRR, 2016
We introduce Concentrated Differential Privacy, a relaxation of Differential Privacy enjoying better accuracy than both pure differential privacy and its popular "(epsilon,delta)" relaxation without compromising on cumulative privacy loss over multiple computations.
Cynthia Dwork, Guy N. Rothblum
openaire   +2 more sources

Discrete Gaussian for Differential Privacy

Journal of Privacy and Confidentiality, 2022
A key tool for building differentially private systems is adding Gaussian noise to the output of a function evaluated on a sensitive dataset. Unfortunately, using a continuous distribution presents several practical challenges. First and foremost, finite computers cannot exactly represent samples from continuous distributions, and previous work has ...
Clément L. Canonne, Gautam Kamath 0001, Thomas Steinke 0002   +2 more
openaire   +7 more sources

Bridging the Loneliness Gap: Depression, Connectivity, and Isolation in Pediatric Oncology Patients and Their Peers

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Loneliness is associated with adverse physical and mental health outcomes and remains understudied in children and adolescents undergoing cancer therapy. Pediatric oncology patients may be at increased risk due to medical isolation and disruption of social networks.
Charlotte N. Stahlfeld, Scott H. Maurer, Michelle D. Watkinson, John Nury, Elise Barberis, Molly C. Mack   +5 more
wiley   +1 more source

Privacy-aware eye tracking using differential privacy

, 2019
With eye tracking being increasingly integrated into virtual and augmented reality (VR/AR) head-mounted displays, preserving users’ privacy is an ever more important, yet under-explored, topic in the eye tracking community. We report a large-scale online
Andreas Bulling (5099876), Inken Hagestedt (17433096), Michael Xuelin Huang (17433264), Julian Steil (17433261)   +3 more
core   +1 more source

The Protection of Data Sharing for Privacy in Financial Vision

Applied Sciences, 2022
The primary motivation is to address difficulties in data interpretation or a reduction in model accuracy. Although differential privacy can provide data privacy guarantees, it also creates problems.
Yi-Ren Wang, Yun-Cheng Tsai
doaj   +1 more source

Central Nervous System Tumors Among Infants in Canada: A Report From CYP‐C

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Central nervous system (CNS) tumors in infants are rare, pose unique clinical challenges, and lack large‐scale evidence‐based data to guide management. This study seeks to describe CNS tumors in Canadian infants and to compare their outcomes with those of older children.
Samuel Sassine, Hallie Coltin, Sylvia Cheng, Lucie Lafay‐Cousin, Vanan Issai Magimairajan, Craig Erker, Stéphanie Vairy, Lynette Bowes, Adam Fleming, Donna Johnston, Sarah McKillop, Roona Sinha, Julie Bennett, Christina Coleman, Laura Wheaton, Shayna Zelcer, Samuele Renzi, Thai Hoa Tran   +17 more
wiley   +1 more source

Privacy and Data Protection Act 2014 [PDF]

, 2014
This report establishes a data security regime for all information held by the Victorian public sector. Authorised Version No. 001 - Privacy and Data Protection Act 2014 - No.
Commissioner for Privacy and Data Protection
core  

Venetoclax‐Based Therapy as a Bridge to Hematopoietic Stem Cell Transplantation in Relapsed or Refractory Pediatric Acute Leukemia

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Relapsed and/or refractory (R/R) pediatric acute leukemia carries a dismal prognosis, largely driven by chemoresistance to conventional salvage therapy. The BH3‐mimetic venetoclax, combined with chemotherapy or hypomethylating agents, has demonstrated efficacy in small clinical trials.
Katherine S. Colman, Deborah Meyran, Vajiranee Malalasekera, Heather Weerdenburg, Janine Campbell, Rachel Conyers, Stacie Wang, Hannah Walker, Seong Lin Khaw, Diane Hanna   +9 more
wiley   +1 more source

Differential Privacy By Sampling

CoRR, 2017
In this paper we present the Sampling Privacy mechanism for privately releasing personal data. Sampling Privacy is a sampling based privacy mechanism that satisfies differential privacy.
Josh Joy, Mario Gerla
openaire   +2 more sources

Survey on differential privacy and its progress

Tongxin xuebao, 2017
With the arrival of the era of big data sharing,data privacy protection issues will be highlighted.Since its introduction in 2006,differential privacy technology has been widely researched in data mining and data publishing.In recent years,Google,Apple ...
Zhi-qiang GAO, Yu-tao WANG
doaj   +2 more sources