research
∙
09/07/2023
Empirical Risk Minimization for Losses without Variance
This paper considers an empirical risk minimization problem under heavy-...
share
research
∙
07/21/2023
Epsilon*: Privacy Metric for Machine Learning Models
We introduce Epsilon*, a new privacy metric for measuring the privacy ri...
research
∙
06/24/2023
Adaptive Privacy Composition for Accuracy-first Mechanisms
In many practical applications of differential privacy, practitioners se...
research
∙
06/08/2023
A Cover Time Study of a non-Markovian Algorithm
Given a traversal algorithm, cover time is the expected number of steps ...
research
∙
11/23/2022
Kernel PCA for multivariate extremes
We propose kernel PCA as a method for analyzing the dependence structure...
research
∙
11/15/2022
On Penalization in Stochastic Multi-armed Bandits
We study an important variant of the stochastic multi-armed bandit (MAB)...
research
∙
08/05/2022
Catoni-style Confidence Sequences under Infinite Variance
In this paper, we provide an extension of confidence sequences for setti...
research
∙
04/16/2022
Detection of Small Holes by the Scale-Invariant Robust Density-Aware Distance (RDAD) Filtration
A novel topological-data-analytical (TDA) method is proposed to distingu...
research
∙
11/15/2021
Spectral learning of multivariate extremes
We propose a spectral clustering algorithm for analyzing the dependence ...
research
∙
09/09/2021
Extreme Bandits using Robust Statistics
We consider a multi-armed bandit problem motivated by situations where o...
research
∙
11/09/2020
Likelihood Inference for Possibly Non-Stationary Processes via Adaptive Overdifferencing
We make a simple observation that facilitates valid likelihood-based inf...
research
∙
06/25/2018
Distance covariance for discretized stochastic processes
Given an iid sequence of pairs of stochastic processes on the unit inter...
research
∙
12/20/2017
