75 citations · 131 across the 12 of their papers we have counts for
12 papers
Revisiting Adversarially Learned Injection Attacks Against Recommender Systems
Jiaxi Tang, Hongyi Wen, Ke Wang
Recommender systems play an important role in modern information and e-commerce applications. While increasing research is dedicated to improving the relevance and diversity of the…
The Differentially Private Lottery Ticket Mechanism
Lovedeep Gondara, Ke Wang, Ricardo Silva Carvalho
We propose the differentially private lottery ticket mechanism (DPLTM). An end-to-end differentially private training paradigm based on the lottery ticket hypothesis. Using "high-q…
Differentially Private Survival Function Estimation
Lovedeep Gondara, Ke Wang
Survival function estimation is used in many disciplines, but it is most common in medical analytics in the form of the Kaplan-Meier estimator. Sensitive data (patient records) is…
Recovering Loss to Followup Information Using Denoising Autoencoders
Lovedeep Gondara, Ke Wang
Loss to followup is a significant issue in healthcare and has serious consequences for a study's validity and cost. Methods available at present for recovering loss to followup inf…
MIDA: Multiple Imputation using Denoising Autoencoders
Lovedeep Gondara, Ke Wang
Missing data is a significant problem impacting all domains. State-of-the-art framework for minimizing missing data bias is multiple imputation, for which the choice of an imputati…
Inferential or Differential: Privacy Laws Dictate
Ke Wang, Peng Wang, Ada Waichee Fu +1
So far, privacy models follow two paradigms. The first paradigm, termed inferential privacy in this paper, focuses on the risk due to statistical inference of sensitive information…