51 citations · 160 across the 19 of their papers we have counts for
7 papers · 1 filter
Privacy-Preserving Conformal Prediction Under Local Differential Privacy
Coby Penso, Bar Mahpud, Jacob Goldberger +1
Conformal prediction (CP) provides sets of candidate classes with a guaranteed probability of containing the true class. However, it typically relies on a calibration set with clea…
A Private Approximation of the 2nd-Moment Matrix of Any Subsamplable Input
Bar Mahpud, Or Sheffet
We study the problem of differentially private second moment estimation and present a new algorithm that achieve strong privacy-utility trade-offs even for worst-case inputs under…
Transfer Learning In Differential Privacy's Hybrid-Model
Refael Kohen, Or Sheffet
The hybrid-model (Avent et al 2017) in Differential Privacy is a an augmentation of the local-model where in addition to N local-agents we are assisted by one special agent who is…
Differentially Private Contextual Linear Bandits
Roshan Shariff, Or Sheffet
We study the contextual linear bandit problem, a version of the standard stochastic multi-armed bandit (MAB) problem where a learner sequentially selects actions to maximize a rewa…
Learning Mixtures of Ranking Models
Pranjal Awasthi, Avrim Blum, Or Sheffet +1
This work concerns learning probabilistic models for ranking data in a heterogeneous population. The specific problem we study is learning the parameters of a Mallows Mixture Model…
Predicting Preference Flips in Commerce Search
Or Sheffet, Nina Mishra, Samuel Ieong
Traditional approaches to ranking in web search follow the paradigm of rank-by-score: a learned function gives each query-URL combination an absolute score and URLs are ranked acco…