5 papers · 1 filter
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…
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…
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance
Sudeep Salgia, Sattar Vakili, Qing Zhao
We consider sequential optimization of an unknown function in a reproducing kernel Hilbert space. We propose a Gaussian process-based algorithm and establish its order-optimal regr…
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization
Sudeep Salgia, Qing Zhao, Sattar Vakili
A framework based on iterative coordinate minimization (CM) is developed for stochastic convex optimization. Given that exact coordinate minimization is impossible due to the unkno…
Stochastic Gradient Descent on a Tree: an Adaptive and Robust Approach to Stochastic Convex Optimization
Sattar Vakili, Sudeep Salgia, Qing Zhao
Online minimization of an unknown convex function over the interval is considered under first-order stochastic bandit feedback, which returns a random realization of the gr…