conftrace_

sample weighting

37 papers

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Co-occurring keywords

label noise (498) noisy label (321) class imbalance (555) convolutional neural network (4226) curriculum learning (633) domain adaptation (4595) label correction (34) stable learning (7) sample re-weighting (9) graph neural network (3962)

Papers

Sample Weighted Incomplete Multimodal Clustering Based on Graph Coarsening Label Extraction AAAI 2026
BidMatch: Boosting Semi-Supervised Learning by Bi-Dimensional Sample Weight Guidance AAAI 2026
ReSURE: Regularizing Supervision Unreliability for Multi-turn Dialogue Fine-tuning EMNLP 2025
COSEE: Consistency-Oriented Signal-Based Early Exiting via Calibrated Sample Weighting Mechanism AAAI 2025
Efficient Annotator Reliability Assessment and Sample Weighting for Knowledge-Based Misinformation Detection on Social Media NAACL 2025
Efficient Annotator Reliability Assessment with EffiARA ACL 2025
Suppressing Uncertainty in Gaze Estimation AAAI 2024
Nearest Neighbor Sampling for Covariate Shift Adaptation JMLR 2024
Exploiting Geometry for Treatment Effect Estimation via Optimal Transport AAAI 2024
Generalized Fake Audio Detection via Deep Stable Learning INTERSPEECH 2024
Learning with Noisy Labels Using Hyperspherical Margin Weighting AAAI 2024
Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial Training CVPR 2024
CoSW: Conditional Sample Weighting for Smoke Segmentation with Label Noise NIPS 2024
Task-aware world model learning with meta weighting via bi-level optimization NIPS 2023
Memorization Weights for Instance Reweighting in Adversarial Training AAAI 2023
How To Prevent the Continuous Damage of Noises To Model Training? CVPR 2023
Learning to Learn from Corrupted Data for Few-Shot Learning IJCAI 2023
Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning AAAI 2023
Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering AAAI 2023
Noise Attention Learning: Enhancing Noise Robustness by Gradient Scaling NIPS 2022
Learning To Learn Across Diverse Data Biases in Deep Face Recognition CVPR 2022
Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data AAAI 2022
Deep Stable Learning for Out-of-Distribution Generalization CVPR 2021
Improving the Performance-Compatibility Tradeoff with Personalized Objective Functions (Student Abstract) AAAI 2021
Adversarial Regression with Doubly Non-negative Weighting Matrices NIPS 2021