48 citations · 147 across the 15 of their papers we have counts for
4 papers · 1 filter
Parameter-Free Locally Differentially Private Stochastic Subgradient Descent
Kwang-Sung Jun, Francesco Orabona
We consider the problem of minimizing a convex risk with stochastic subgradients guaranteeing -locally differentially private (-LDP). While it has been shown that stochastic…
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration
Kwang-Sung Jun, Ashok Cutkosky, Francesco Orabona
In this paper, we consider the nonparametric least square regression in a Reproducing Kernel Hilbert Space (RKHS). We propose a new randomized algorithm that has optimal generaliza…
Parameter-Free Online Convex Optimization with Sub-Exponential Noise
Kwang-Sung Jun, Francesco Orabona
We consider the problem of unconstrained online convex optimization (OCO) with sub-exponential noise, a strictly more general problem than the standard OCO. In this setting, the le…
Bilinear Bandits with Low-rank Structure
Kwang-Sung Jun, Rebecca Willett, Stephen Wright +1
We introduce the bilinear bandit problem with low-rank structure in which an action takes the form of a pair of arms from two different entity types, and the reward is a bilinear f…