Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

18 October 2016

Papers citing "Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data"

23 / 23 papers shown

Title
A Case Study Exploring the Current Landscape of Synthetic Medical Record Generation with Commercial LLMs Yihan Lin Zhirong Bella Yu Simon Lee SyDa 92 0 0 20 Apr 2025
DP-GPL: Differentially Private Graph Prompt Learning Jing Xu Franziska Boenisch Iyiola Emmanuel Olatunji Adam Dziedzic AAML 84 0 0 13 Mar 2025
Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models Martin Pawelczyk Lillian Sun Zhenting Qi Aounon Kumar Himabindu Lakkaraju 98 2 0 03 Jan 2025
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios Sangyeon Yoon Wonje Jeung Albert No 116 0 0 02 Dec 2024
PFGuard: A Generative Framework with Privacy and Fairness Safeguards Soyeon Kim Yuji Roh Geon Heo Steven Euijong Whang 58 0 0 03 Oct 2024
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey Chaoyu Zhang Shaoyu Li AILaw 84 4 0 25 Feb 2024
On the Byzantine-Resilience of Distillation-Based Federated Learning Christophe Roux Max Zimmer Sebastian Pokutta AAML 93 1 0 19 Feb 2024
Hot PATE: Private Aggregation of Distributions for Diverse Task Edith Cohen Benjamin Cohen-Wang Xin Lyu Jelani Nelson Tamas Sarlos Uri Stemmer 77 3 0 04 Dec 2023
PRIMO: Private Regression in Multiple Outcomes Seth Neel 45 0 0 07 Mar 2023
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers Ananth Balashankar Alyssa Lees Chris Welty L. Subramanian 41 21 0 30 Oct 2019
Renyi Differential Privacy Ilya Mironov 53 1,243 0 24 Feb 2017
Missing Data Imputation for Supervised Learning Jason Poulos Rafael Valle 41 62 0 28 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 170 6,069 0 01 Jul 2016
Smart Reply: Automated Response Suggestion for Email Anjuli Kannan Karol Kurach Sujith Ravi Tobias Kaufmann Andrew Tomkins ... G. Corrado László Lukács Marina Ganea Peter Young Vivek Ramavajjala VLM 39 309 0 15 Jun 2016
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 371 8,999 0 10 Jun 2016
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 55 823 0 06 May 2016
Concentrated Differential Privacy Cynthia Dwork G. Rothblum 50 446 0 06 Mar 2016
Learning Privately from Multiparty Data Jihun Hamm Yingjun Cao M. Belkin FedML 33 165 0 10 Feb 2016
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 238 19,523 0 09 Mar 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 59 1,977 0 25 Jul 2014
Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds Raef Bassily Adam D. Smith Abhradeep Thakurta FedML 95 371 0 27 May 2014
Privacy Aware Learning John C. Duchi Michael I. Jordan Martin J. Wainwright 131 290 0 07 Oct 2012
Differentially Private Empirical Risk Minimization Kamalika Chaudhuri C. Monteleoni Anand D. Sarwate 93 1,482 0 01 Dec 2009