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Robustness

529 directly classified papers

Papers per year

Papers

Reliable learning in challenging environments NIPS 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NIPS 2023
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients NIPS 2023
QuadAttac$K$: A Quadratic Programming Approach to Learning Ordered Top-$K$ Adversarial Attacks NIPS 2023
Conservative State Value Estimation for Offline Reinforcement Learning NIPS 2023
What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners? NIPS 2023
Corruption-Robust Offline Reinforcement Learning with General Function Approximation NIPS 2023
On Private and Robust Bandits NIPS 2023
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization NIPS 2023
Characterizing the Optimal $0-1$ Loss for Multi-class Classification with a Test-time Attacker NIPS 2023
Use perturbations when learning from explanations NIPS 2023
Cross-modal Active Complementary Learning with Self-refining Correspondence NIPS 2023
Byzantine-Tolerant Methods for Distributed Variational Inequalities NIPS 2023
Understanding the Robustness of 3D Object Detection With Bird's-Eye-View Representations in Autonomous Driving CVPR 2023
Generalist: Decoupling Natural and Robust Generalization CVPR 2023
Outlier-Robust Gromov-Wasserstein for Graph Data NIPS 2023
Fast Bellman Updates for Wasserstein Distributionally Robust MDPs NIPS 2023
StyLess: Boosting the Transferability of Adversarial Examples CVPR 2023
A Large-Scale Robustness Analysis of Video Action Recognition Models CVPR 2023
Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More NIPS 2023
Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets CVPR 2023
Introducing Competition To Boost the Transferability of Targeted Adversarial Examples Through Clean Feature Mixup CVPR 2023
Window-Based Distribution Shift Detection for Deep Neural Networks NIPS 2023
H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets NIPS 2023
TrojDiff: Trojan Attacks on Diffusion Models With Diverse Targets CVPR 2023