Learning from Noisy Labels with Distillation

7 March 2017

Papers citing "Learning from Noisy Labels with Distillation"

50 / 284 papers shown

Title
Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing Adel Javanmard Rudrajit Das Alessandro Epasto Vahab Mirrokni 51 0 0 21 May 2025
CARE: Compatibility-Aware Incentive Mechanisms for Federated Learning with Budgeted Requesters Xiang Liu Hau Chan Minming Li Xianlong Zeng Chenchen Fu Weiwei Wu FedML 43 0 0 22 Apr 2025
Simultaneous Automatic Picking and Manual Picking Refinement for First-Break Haowen Bai Zixiang Zhao Jiangshe Zhang Yukun Cui Chunxia Zhang Zhenbo Guo Yongjun Wang 71 1 0 03 Feb 2025
Towards Fault Tolerance in Multi-Agent Reinforcement Learning Yuchen Shi Huaxin Pei Liang Feng Jianming Hu Dingyi Yao 87 0 0 30 Nov 2024
Underwater Object Detection in the Era of Artificial Intelligence: Current, Challenge, and Future Long Chen Yuzhi Huang Junyu Dong Qi Xu Sam Kwong Huimin Lu Huchuan Lu Chongyi Li 43 2 0 08 Oct 2024
Implicit to Explicit Entropy Regularization: Benchmarking ViT Fine-tuning under Noisy Labels Maria Marrium Arif Mahmood Mohammed Bennamoun NoLa AAML 53 0 0 05 Oct 2024
Granular-ball Representation Learning for Deep CNN on Learning with Label Noise Dawei Dai Hao Zhu Shuyin Xia Guoyin Wang SSL 37 1 0 05 Sep 2024
Disentangled Noisy Correspondence Learning Zhuohang Dang Minnan Luo Jihong Wang Chengyou Jia Haochen Han Herun Wan Guang Dai Xiaojun Chang Jingdong Wang 42 0 0 10 Aug 2024
Make a Strong Teacher with Label Assistance: A Novel Knowledge Distillation Approach for Semantic Segmentation Shoumeng Qiu Jie Chen Xinrun Li Ru Wan Xiangyang Xue Jian Pu VLM 65 3 0 18 Jul 2024
Understanding the Gains from Repeated Self-Distillation Divyansh Pareek Simon S. Du Sewoong Oh 63 5 0 05 Jul 2024
Retraining with Predicted Hard Labels Provably Increases Model Accuracy Rudrajit Das Inderjit S Dhillon Alessandro Epasto Adel Javanmard Jieming Mao Vahab Mirrokni Sujay Sanghavi Peilin Zhong 61 2 0 17 Jun 2024
Data-Efficient and Robust Task Selection for Meta-Learning Donglin Zhan James Anderson OOD 48 2 0 11 May 2024
Potential Energy based Mixture Model for Noisy Label Learning Zijia Wang Wenbin Yang Zhisong Liu Zhen Jia NoLa 34 0 0 02 May 2024
Promoting CNNs with Cross-Architecture Knowledge Distillation for Efficient Monocular Depth Estimation Zhimeng Zheng Tao Huang Gongsheng Li Zuyi Wang 64 2 0 25 Apr 2024
Dynamic Temperature Knowledge Distillation Yukang Wei Yu Bai 55 4 0 19 Apr 2024
Extracting Clean and Balanced Subset for Noisy Long-tailed Classification Zhuo Li He Zhao Zhen Li Tongliang Liu Dandan Guo Xiang Wan NoLa 48 1 0 10 Apr 2024
An Interpretable Power System Transient Stability Assessment Method with Expert Guiding Neural-Regression-Tree Hanxuan Wang Na Lu Zixuan Wang Jiacheng Liu Jun Liu 30 0 0 03 Apr 2024
Tackling Noisy Labels with Network Parameter Additive Decomposition Jingyi Wang Xiaobo Xia Long Lan Xinghao Wu Jun-chen Yu Wenjing Yang Bo Han Tongliang Liu NoLa 51 8 0 20 Mar 2024
Automated data processing and feature engineering for deep learning and big data applications: a survey A. Mumuni F. Mumuni TPM 51 51 0 18 Mar 2024
$ROG$_{PL}$: Robust Open-Set Graph Learning via Region-Based Prototype Learning$ ROG $_{PL}$ : Robust Open-Set Graph Learning via Region-Based Prototype Learning Qin Zhang Xiaowei Li Jiexin Lu Liping Qiu Shirui Pan Xiaojun Chen Junyang Chen 68 1 0 28 Feb 2024
Learning under Label Noise through Few-Shot Human-in-the-Loop Refinement Aaqib Saeed Dimitris Spathis Jungwoo Oh Edward Choi Ali Etemad NoLa 36 2 0 25 Jan 2024
Pseudo-label Correction for Instance-dependent Noise Using Teacher-student Framework Eugene Kim NoLa 50 0 0 24 Nov 2023
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models Zhaowei Zhu Jialu Wang Hao Cheng Yang Liu 38 16 0 19 Nov 2023
Trustworthy Large Models in Vision: A Survey Ziyan Guo Li Xu Jun Liu MU 66 0 0 16 Nov 2023
Distilling Efficient Vision Transformers from CNNs for Semantic Segmentation Xueye Zheng Yunhao Luo Pengyuan Zhou Lin Wang 35 14 0 11 Oct 2023
Expert Uncertainty and Severity Aware Chest X-Ray Classification by Multi-Relationship Graph Learning Mengliang Zhang Xinyue Hu Lin Gu Liangchen Liu Kazuma Kobayashi Tatsuya Harada Ronald M. Summers Yingying Zhu 56 3 0 06 Sep 2023
Regularly Truncated M-estimators for Learning with Noisy Labels Xiaobo Xia Pengqian Lu Chen Gong Bo Han Jun-chen Yu Jun Yu Tongliang Liu NoLa 43 10 0 02 Sep 2023
The Quest of Finding the Antidote to Sparse Double Descent Victor Quétu Marta Milovanović 60 0 0 31 Aug 2023
QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection Yifan Zhang Zhen Dong Huanrui Yang Ming Lu Cheng-Ching Tseng Yuan Du Kurt Keutzer Li Du Shanghang Zhang MQ 39 9 0 21 Aug 2023
Feature Noise Boosts DNN Generalization under Label Noise Lu Zeng Xuan Chen Xiaoshuang Shi Jikang Cheng MLT NoLa 41 2 0 03 Aug 2023
Investigating the Learning Behaviour of In-context Learning: A Comparison with Supervised Learning Xindi Wang Yufei Wang Can Xu Xiubo Geng Bowen Zhang Chongyang Tao Frank Rudzicz Robert E. Mercer Daxin Jiang 38 11 0 28 Jul 2023
Why Is Prompt Tuning for Vision-Language Models Robust to Noisy Labels? Cheng-En Wu Yu Tian Haichao Yu Heng Wang Pedro Morgado Yu Hen Hu Linjie Yang NoLa VPVLM VLM 38 19 0 22 Jul 2023
Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features Cian Eastwood Shashank Singh Andrei Liviu Nicolicioiu Marin Vlastelica Julius von Kügelgen Bernhard Schölkopf OOD 47 19 0 19 Jul 2023
TADIL: Task-Agnostic Domain-Incremental Learning through Task-ID Inference using Transformer Nearest-Centroid Embeddings Gusseppe Bravo Rocca Peini Liu Jordi Guitart Ajay Dholakia David Ellison 37 1 0 21 Jun 2023
LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge Integration Siqi Wang Bryan A. Plummer 44 2 0 20 Jun 2023
Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal Anastasiia Sedova Lena Zellinger Benjamin Roth 29 2 0 07 Jun 2023
UADB: Unsupervised Anomaly Detection Booster Hangting Ye Zhining Liu Xinyi Shen Wei Cao Shun Zheng Xiaofan Gui Huishuai Zhang Yi Chang Jiang Bian 42 3 0 03 Jun 2023
Knowledge Distillation Performs Partial Variance Reduction M. Safaryan Alexandra Peste Dan Alistarh 45 6 0 27 May 2023
TaxoKnow: Taxonomy as Prior Knowledge in the Loss Function of Multi-class Classification Mohsen Pourvali Yao Meng Chen Sheng Yangzhou Du 20 0 0 24 May 2023
Handling Realistic Label Noise in BERT Text Classification M. Agro Hanan Aldarmaki NoLa 44 3 0 23 May 2023
Complementary Domain Adaptation and Generalization for Unsupervised Continual Domain Shift Learning Won-Yong Cho Jinha Park Taesup Kim CLL 73 5 0 28 Mar 2023
BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity Consistency Shuo Yang Zhaopan Xu Kai Wang Yang You Huanjin Yao Tongliang Liu Min Xu 50 15 0 22 Mar 2023
DSD $^2$ : Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free? Victor Quétu Enzo Tartaglione 42 7 0 02 Mar 2023
Self-Supervised Monocular Depth Estimation with Self-Reference Distillation and Disparity Offset Refinement Zhong Liu Ran Li Shuwei Shao Xingming Wu Weihai Chen MDE 40 30 0 20 Feb 2023
Latent Class-Conditional Noise Model Jiangchao Yao Bo Han Zhihan Zhou Ya Zhang Ivor W. Tsang NoLa BDL 40 8 0 19 Feb 2023
Learning From Biased Soft Labels Hua Yuan Ning Xu Yuge Shi Xin Geng Yong Rui FedML 42 6 0 16 Feb 2023
Understanding Self-Distillation in the Presence of Label Noise Rudrajit Das Sujay Sanghavi 62 16 0 30 Jan 2023
Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training Filip Radenovic Abhimanyu Dubey Abhishek Kadian Todor Mihaylov Simon Vandenhende Yash J. Patel Y. Wen Vignesh Ramanathan D. Mahajan VLM 45 82 0 05 Jan 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels Yikai Wang Yanwei Fu Xinwei Sun NoLa 57 8 0 02 Jan 2023
BD-KD: Balancing the Divergences for Online Knowledge Distillation Ibtihel Amara N. Sepahvand B. Meyer W. Gross J. Clark 50 2 0 25 Dec 2022