402 citations · 843 across the 16 of their papers we have counts for
4 papers · 1 filter
ABC: Efficient Selection of Machine Learning Configuration on Large Dataset
Silu Huang, Chi Wang, Bolin Ding +1
A machine learning configuration refers to a combination of preprocessor, learner, and hyperparameters. Given a set of configurations and a large dataset randomly split into traini…
Towards Differentially Private Truth Discovery for Crowd Sensing Systems
Yaliang Li, Houping Xiao, Zhan Qin +5
Nowadays, crowd sensing becomes increasingly more popular due to the ubiquitous usage of mobile devices. However, the quality of such human-generated sensory data varies significan…
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Joshua Allen, Bolin Ding, Janardhan Kulkarni +3
Differential privacy has emerged as the main definition for private data analysis and machine learning. The {\em global} model of differential privacy, which assumes that users tru…
Comparing Population Means under Local Differential Privacy: with Significance and Power
Bolin Ding, Harsha Nori, Paul Li +1
A statistical hypothesis test determines whether a hypothesis should be rejected based on samples from populations. In particular, randomized controlled experiments (or A/B testing…