Distributionally robust optimization: A review
H Rahimian, S Mehrotra - ar** attacks via randomized smoothing
E Rosenfeld, E Winston… - … on Machine Learning, 2020 - proceedings.mlr.press
Abstract Machine learning algorithms are known to be susceptible to data poisoning attacks,
where an adversary manipulates the training data to degrade performance of the resulting …
where an adversary manipulates the training data to degrade performance of the resulting …
Finite-sample guarantees for Wasserstein distributionally robust optimization: Breaking the curse of dimensionality
R Gao - Operations Research, 2023 - pubsonline.informs.org
Wasserstein distributionally robust optimization (DRO) aims to find robust and generalizable
solutions by hedging against data perturbations in Wasserstein distance. Despite its recent …
solutions by hedging against data perturbations in Wasserstein distance. Despite its recent …
[PDF][PDF] Learning-based Practical Smartphone Eavesdrop** with Built-in Accelerometer.
Motion sensors on current smartphones have been exploited for audio eavesdrop** due
to their sensitivity to vibrations. However, this threat is considered low-risk because of two …
to their sensitivity to vibrations. However, this threat is considered low-risk because of two …
Distributionally robust learning
R Chen, IC Paschalidis - Foundations and Trends® in …, 2020 - nowpublishers.com
This monograph develops a comprehensive statistical learning framework that is robust to
(distributional) perturbations in the data using Distributionally Robust Optimization (DRO) …
(distributional) perturbations in the data using Distributionally Robust Optimization (DRO) …
Wasserstein distributionally robust stochastic control: A data-driven approach
I Yang - IEEE Transactions on Automatic Control, 2020 - ieeexplore.ieee.org
Standard stochastic control methods assume that the probability distribution of uncertain
variables is available. Unfortunately, in practice, obtaining accurate distribution information …
variables is available. Unfortunately, in practice, obtaining accurate distribution information …