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Robust Learning

68 directly classified papers

Papers per year

Papers

Learning from Noisy Labels via Self-Taught On-the-Fly Meta Loss Rescaling AAAI 2025
Two Challenges, One Solution: Robust Multimodal Learning through Dynamic Modality Recognition and Enhancement EMNLP 2025
Federated Learning with Extremely Noisy Clients via Negative Distillation AAAI 2024
Collaborative Refining for Learning from Inaccurate Labels NIPS 2024
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions NIPS 2024
Efficient Overshadowed Entity Disambiguation by Mitigating Shortcut Learning EMNLP 2024
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models NIPS 2024
Robust variance-regularized risk minimization with concomitant scaling AISTATS 2024
Enhancing Multi-Label Text Classification under Label-Dependent Noise: A Label-Specific Denoising Framework EMNLP 2024
NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition EMNLP 2024
Learning to Reweight for Generalizable Graph Neural Network AAAI 2024
Active Reinforcement Learning for Robust Building Control AAAI 2024
NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise NIPS 2024
L2B: Learning to Bootstrap Robust Models for Combating Label Noise CVPR 2024
Learning from Noisy Labels via Conditional Distributionally Robust Optimization NIPS 2024
Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise AAAI 2024
Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning CVPR 2023
Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning AAAI 2023
A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise AAAI 2023
Combating Bilateral Edge Noise for Robust Link Prediction NIPS 2023
Robust Domain Adaptation for Machine Reading Comprehension AAAI 2023
Corruption-Tolerant Algorithms for Generalized Linear Models AAAI 2023
Multiple Robust Learning for Recommendation AAAI 2023
Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints AISTATS 2023
Denoising after Entropy-Based Debiasing a Robust Training Method for Dataset Bias with Noisy Labels AAAI 2023