73 citations · 439 across the 61 of their papers we have counts for
5 papers · 1 filter
Empirical Risk Minimization for Losses without Variance
Guanhua Fang, Ping Li, Gennady Samorodnitsky
This paper considers an empirical risk minimization problem under heavy-tailed settings, where data does not have finite variance, but only has -th moment with . In…
Kernel PCA for multivariate extremes
Marco Avella-Medina, Richard A. Davis, Gennady Samorodnitsky
We propose kernel PCA as a method for analyzing the dependence structure of multivariate extremes and demonstrate that it can be a powerful tool for clustering and dimension reduct…
On Penalization in Stochastic Multi-armed Bandits
Guanhua Fang, Ping Li, Gennady Samorodnitsky
We study an important variant of the stochastic multi-armed bandit (MAB) problem, which takes penalization into consideration. Instead of directly maximizing cumulative expected re…
Spectral learning of multivariate extremes
Marco Avella Medina, Richard A. Davis, Gennady Samorodnitsky
We propose a spectral clustering algorithm for analyzing the dependence structure of multivariate extremes. More specifically, we focus on the asymptotic dependence of multivariate…
Extreme Bandits using Robust Statistics
Sujay Bhatt, Ping Li, Gennady Samorodnitsky
We consider a multi-armed bandit problem motivated by situations where only the extreme values, as opposed to expected values in the classical bandit setting, are of interest. We p…