3 citations · 8 across the 11 of their papers we have counts for
4 papers · 1 filter
End-to-End Differential Privacy in Training Deep Neural Network Classifiers
Huaiyuan Rao, Calvin Hawkins, Alexander Benvenuti +1
Differentially private machine learning enables model training on sensitive data while ensuring that individual data is unlikely to be recoverable from the parameters of the result…
Online Scalarization in Vector-Valued Games
Ehsan Asadollahi, Calvin Hawkins, Matthew Hale
We study repeated multi-player vector-valued games in which a player observes a payoff vector each round and evaluates outcomes through linear scalarizations of those vectors. Diff…
Differentially Private Data-Driven Markov Chain Modeling
Alexander Benvenuti, Brandon Fallin, Calvin Hawkins +4
Markov chains model a wide range of user behaviors. However, generating accurate Markov chain models requires substantial user data, and sharing these models without privacy protec…
Approximately Optimal Multi-Stream Quickest Change Detection
Joshua Kartzman, Calvin Hawkins, Matthew Hale
This paper considers the constrained sampling multi-stream quickest change detection problem, also known as the bandit quickest change detection problem. One stream contains a chan…