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Robustness

529 directly classified papers

Papers per year

Papers

Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering NIPS 2019
On Robustness of Principal Component Regression NIPS 2019
Selecting Optimal Decisions via Distributionally Robust Nearest-Neighbor Regression NIPS 2019
On the Hardness of Robust Classification NIPS 2019
Learning from brains how to regularize machines NIPS 2019
Distributionally Robust Optimization and Generalization in Kernel Methods NIPS 2019
A First-Order Algorithmic Framework for Distributionally Robust Logistic Regression NIPS 2019
Lower Bounds on Adversarial Robustness from Optimal Transport NIPS 2019
Improving the Robustness of Question Answering Systems to Question Paraphrasing ACL 2019
Don’t Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference ACL 2019
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution NIPS 2018
Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors CVPR 2018
Defense Against Universal Adversarial Perturbations CVPR 2018
Towards Robust Detection of Adversarial Examples NIPS 2018
Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms NIPS 2018
Thwarting Adversarial Examples: An $L_0$-Robust Sparse Fourier Transform NIPS 2018
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets NIPS 2018
Training a Neural Network in a Low-Resource Setting on Automatically Annotated Noisy Data ACL 2018
Adversarially Robust Generalization Requires More Data NIPS 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness NIPS 2018
Wasserstein Distributionally Robust Kalman Filtering NIPS 2018
Lower bounds on the robustness to adversarial perturbations NIPS 2017
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks NIPS 2017
Certified Defenses for Data Poisoning Attacks NIPS 2017
Robust Adversarial Reinforcement Learning ICML 2017