conftrace_

label noise

498 papers

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Co-occurring keywords

noisy label (321) noisy label learning (163) deep neural network (1803) semi-supervised learning (2341) weakly supervised learning (1328) text classification (6793) image classification (1944) data augmentation (3052) representation learning (6206) active learning (1301)

Papers

Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimization ICML 2023
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML 2023
Smoothly Giving up: Robustness for Simple Models AISTATS 2023
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity ICML 2023
How To Prevent the Continuous Damage of Noises To Model Training? CVPR 2023
A Path to Simpler Models Starts With Noise NIPS 2023
Semi-Supervised Domain Adaptation With Source Label Adaptation CVPR 2023
Tester-Learners for Halfspaces: Universal Algorithms NIPS 2023
Semi-Verified PAC Learning from the Crowd AISTATS 2023
Adaptive Textual Label Noise Learning based on Pre-trained Models EMNLP 2023
Binary Classification with Confidence Difference NIPS 2023
Graph-Based Self-Learning for Robust Person Re-Identification WACV 2023
When does Privileged information Explain Away Label Noise? ICML 2023
CrossSplit: Mitigating Label Noise Memorization through Data Splitting ICML 2023
Automated Classification of Model Errors on ImageNet NIPS 2023
Retaining Beneficial Information from Detrimental Data for Neural Network Repair NIPS 2023
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks ICML 2023
Learning to Correct Noisy Labels for Fine-Grained Entity Typing via Co-Prediction Prompt Tuning EMNLP 2023
Regression with Sensor Data Containing Incomplete Observations ICML 2023
Weaker Than You Think: A Critical Look at Weakly Supervised Learning ACL 2023
Understanding Self-Distillation in the Presence of Label Noise ICML 2023
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy NIPS 2023
JointMatch: A Unified Approach for Diverse and Collaborative Pseudo-Labeling to Semi-Supervised Text Classification EMNLP 2023
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? NIPS 2023
CTW: Confident Time-Warping for Time-Series Label-Noise Learning IJCAI 2023