Probabilistically Robust Learning: Balancing Average- and Worst-case
Performance

Probabilistically Robust Learning: Balancing Average- and Worst-case Performance

2 February 2022

Alexander Robey

Luiz F. O. Chamon

George J. Pappas

Papers citing "Probabilistically Robust Learning: Balancing Average- and Worst-case Performance"

12 / 12 papers shown

Title
On Tradeoffs in Learning-Augmented Algorithms Ziyad Benomar Vianney Perchet 38 1 0 22 Jan 2025
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness Maayan Ehrenberg Roy Ganz Nir Rosenfeld AAML 37 0 0 17 Jun 2024
Fast Computation of Superquantile-Constrained Optimization Through Implicit Scenario Reduction Jake Roth Ying Cui 26 2 0 13 May 2024
Resilient Constrained Learning Ignacio Hounie Alejandro Ribeiro Luiz F. O. Chamon 21 9 0 04 Jun 2023
Rank-based Decomposable Losses in Machine Learning: A Survey Shu Hu Xin Wang Siwei Lyu 26 32 0 18 Jul 2022
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy R. Olivier Bhiksha Raj AAML 29 5 0 08 Jul 2022
Adversarial Robustness with Semi-Infinite Constrained Learning Alexander Robey Luiz F. O. Chamon George J. Pappas Hamed Hassani Alejandro Ribeiro AAML OOD 113 42 0 29 Oct 2021
A Survey of Learning Criteria Going Beyond the Usual Risk Matthew J. Holland Kazuki Tanabe FaML 22 4 0 11 Oct 2021
On Tilted Losses in Machine Learning: Theory and Applications Tian Li Ahmad Beirami Maziar Sanjabi Virginia Smith 47 38 0 13 Sep 2021
Consistent Non-Parametric Methods for Maximizing Robustness Robi Bhattacharjee Kamalika Chaudhuri AAML 39 8 0 18 Feb 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 217 675 0 19 Oct 2020
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach Yinlam Chow Aviv Tamar Shie Mannor Marco Pavone 62 310 0 06 Jun 2015