193 citations · 234 across the 3 of their papers we have counts for
3 papers
cs.LG2014★ 193 cited
Differential Privacy and Machine Learning: a Survey and Review
Zhanglong Ji, Zachary C. Lipton, Charles Elkan
The objective of machine learning is to extract useful information from data, while privacy is preserved by concealing information. Thus it seems hard to reconcile these competing…
cs.LG2012★ 34 cited
Predicting accurate probabilities with a ranking loss
Aditya Menon, Xiaoqian Jiang, Shankar Vembu +2
In many real-world applications of machine learning classifiers, it is essential to predict the probability of an example belonging to a particular class. This paper proposes a sim…
cs.LG2010★ 7 cited
Dyadic Prediction Using a Latent Feature Log-Linear Model
Aditya Krishna Menon, Charles Elkan
In dyadic prediction, labels must be predicted for pairs (dyads) whose members possess unique identifiers and, sometimes, additional features called side-information. Special cases…