4 citations · 6 across the 2 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.LG2018
Risk-Averse Stochastic Convex Bandit
Adrian Rivera Cardoso, Huan Xu
Motivated by applications in clinical trials and finance, we study the problem of online convex optimization (with bandit feedback) where the decision maker is risk-averse. We prov…
cs.DS2018
Differentially Private Online Submodular Optimization
Adrian Rivera Cardoso, Rachel Cummings
In this paper we develop the first algorithms for online submodular minimization that preserve differential privacy under full information feedback and bandit feedback. A sequence…
stat.ML2018
The Online Saddle Point Problem and Online Convex Optimization with Knapsacks
Adrian Rivera, He Wang, Huan Xu
We study the online saddle point problem, an online learning problem where at each iteration a pair of actions need to be chosen without knowledge of the current and future (convex…