← Learning Types
Machine Learning › Learning Types ›

Robustness

529 directly classified papers

Papers per year

Papers

Robust Bandit Learning with Imperfect Context AAAI 2021
Outlier Impact Characterization for Time Series Data AAAI 2021
Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes AAAI 2021
Semantics Altering Modifications for Evaluating Comprehension in Machine Reading AAAI 2021
Role of Optimizer on Network Fine-tuning for Adversarial Robustness (Student Abstract) AAAI 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses NIPS 2021
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery NIPS 2021
Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch NIPS 2021
ReLU Regression with Massart Noise NIPS 2021
Not All Low-Pass Filters are Robust in Graph Convolutional Networks NIPS 2021
Interpolation can hurt robust generalization even when there is no noise NIPS 2021
Probabilistic Margins for Instance Reweighting in Adversarial Training NIPS 2021
Adversarially Robust Change Point Detection NIPS 2021
Twice regularized MDPs and the equivalence between robustness and regularization NIPS 2021
Robust Learning of Optimal Auctions NIPS 2021
Evaluating model performance under worst-case subpopulations NIPS 2021
Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks NIPS 2021
Evaluating Models’ Local Decision Boundaries via Contrast Sets EMNLP 2020
Backpropagating Linearly Improves Transferability of Adversarial Examples NIPS 2020
Robust Meta-learning for Mixed Linear Regression with Small Batches NIPS 2020
Certifying Confidence via Randomized Smoothing NIPS 2020
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks NIPS 2020
Large-Scale Methods for Distributionally Robust Optimization NIPS 2020
Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery NIPS 2020
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization NIPS 2020