3 papers
stat.ML2025
Differential Privacy in Kernelized Contextual Bandits via Random Projections
Nikola Pavlovic, Sudeep Salgia, Qing Zhao
We consider the problem of contextual kernel bandits with stochastic contexts, where the underlying reward function belongs to a known Reproducing Kernel Hilbert Space. We study th…
stat.ML2025
Differentially Private Kernelized Contextual Bandits
Nikola Pavlovic, Sudeep Salgia, Qing Zhao
We consider the problem of contextual kernel bandits with stochastic contexts, where the underlying reward function belongs to a known Reproducing Kernel Hilbert Space (RKHS). We s…
cs.LG2025
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization
Sudeep Salgia, Nikola Pavlovic, Yuejie Chi +1
We consider the problem of differentially private stochastic convex optimization (DP-SCO) in a distributed setting with clients, where each of them has a local dataset of i…