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Robustness

529 directly classified papers

Papers per year

Papers

Single-Step Adversarial Training With Dropout Scheduling CVPR 2020
Evaluating adversarial attacks against multiple fact verification systems EMNLP 2019
Robustness Guarantees for Bayesian Inference with Gaussian Processes AAAI 2019
What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks AAAI 2019
Sensitivity Analysis of Deep Neural Networks AAAI 2019
Verifying Robustness of Gradient Boosted Models AAAI 2019
Improving Transferability of Adversarial Examples With Input Diversity CVPR 2019
Robust Ordinal Embedding from Contaminated Relative Comparisons AAAI 2019
Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text Classification EMNLP 2019
Robustness Verification of Tree-based Models NIPS 2019
Adversarial Examples Are Not Bugs, They Are Features NIPS 2019
Certifiable Robustness to Graph Perturbations NIPS 2019
Outlier-robust estimation of a sparse linear model using $\ell_1$-penalized Huber's $M$-estimator NIPS 2019
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers NIPS 2019
Robustness to Capitalization Errors in Named Entity Recognition EMNLP 2019
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual EMNLP 2019
Separate to Adapt: Open Set Domain Adaptation via Progressive Separation CVPR 2019
Robust Subspace Clustering With Independent and Piecewise Identically Distributed Noise Modeling CVPR 2019
Retrieval-Augmented Convolutional Neural Networks Against Adversarial Examples CVPR 2019
Robustness Verification of Classification Deep Neural Networks via Linear Programming CVPR 2019
Iterative Least Trimmed Squares for Mixed Linear Regression NIPS 2019
Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs NIPS 2019
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection NIPS 2019
A Family of Robust Stochastic Operators for Reinforcement Learning NIPS 2019
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty NIPS 2019