Who Said What: Modeling Individual Labelers Improves Classification

26 March 2017

Papers citing "Who Said What: Modeling Individual Labelers Improves Classification"

37 / 37 papers shown

Title
LoD: Loss-difference OOD Detection by Intentionally Label-Noisifying Unlabeled Wild Data Chuanxing Geng Qifei Li Xinrui Wang Dong Liang Songcan Chen Pong C. Yuen 24 0 0 19 May 2025
Annotator Consensus Prediction for Medical Image Segmentation with Diffusion Models Tomer Amit Shmuel Shichrur Tal Shaharabany Lior Wolf MedIm DiffM 51 9 0 15 Jun 2023
Multi-annotator Deep Learning: A Probabilistic Framework for Classification M. Herde Denis Huseljic Bernhard Sick 40 9 0 05 Apr 2023
Learning from Noisy Crowd Labels with Logics Zhijun Chen Hailong Sun Haoqian He Pengpeng Chen NoLa NAI 37 7 0 13 Feb 2023
Learning Confident Classifiers in the Presence of Label Noise Asma Ahmed Hashmi Aigerim Zhumabayeva Nikita Kotelevskii A. Agafonov Mohammad Yaqub Maxim Panov Martin Takávc NoLa 67 2 0 02 Jan 2023
Sources of Noise in Dialogue and How to Deal with Them Derek Chen Zhou Yu 34 2 0 06 Dec 2022
Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters Junde Wu Huihui Fang Yehui Yang Yuanpei Liu Jing Gao Lixin Duan Weihua Yang Yanwu Xu 23 2 0 01 Dec 2022
A Semi-Supervised Algorithm for Improving the Consistency of Crowdsourced Datasets: The COVID-19 Case Study on Respiratory Disorder Classification Lara Orlandic T. Teijeiro David Atienza 49 9 0 09 Sep 2022
Calibrate the inter-observer segmentation uncertainty via diagnosis-first principle Junde Wu Huihui Fang Hoayi Xiong Lixin Duan Mingkui Tan Weihua Yang Huiying Liu Yanwu Xu MedIm 53 1 0 05 Aug 2022
Learning from Multiple Annotator Noisy Labels via Sample-wise Label Fusion Zhengqi Gao Fan-Keng Sun Ming-Hsuan Yang Sucheng Ren Zikai Xiong Marc Engeler Antonio Burazer L. Wildling Lucani E. Daniel Duane S. Boning NoLa 41 15 0 22 Jul 2022
Mimetic Models: Ethical Implications of AI that Acts Like You Reid McIlroy-Young Jon M. Kleinberg S. Sen Solon Barocas Ashton Anderson 18 16 0 19 Jul 2022
Stability of Weighted Majority Voting under Estimated Weights Shaojie Bai Dongxia Wang Tim Muller Peng Cheng Jiming Chen 37 0 0 13 Jul 2022
Clean or Annotate: How to Spend a Limited Data Collection Budget Derek Chen Zhou Yu Samuel R. Bowman 39 13 0 15 Oct 2021
Creating Training Sets via Weak Indirect Supervision Jieyu Zhang Bohan Wang Xiangchen Song Yujing Wang Yaming Yang Jing Bai Alexander Ratner OffRL 54 17 0 07 Oct 2021
Truth Discovery in Sequence Labels from Crowds Nasim Sabetpour Adithya Kulkarni Sihong Xie Qi Li 39 16 0 09 Sep 2021
ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classification Ralf Raumanns Gerard Schouten Max Joosten J. Pluim Veronika Cheplygina 19 5 0 27 Jul 2021
End-to-End Weak Supervision Salva Rühling Cachay Benedikt Boecking A. Dubrawski NoLa 33 40 0 05 Jul 2021
Deep Learning for EEG Seizure Detection in Preterm Infants Alison O'Shea Rehan Ahmed G. Lightbody S. Mathieson Elena Pavlidis Rhodri O Lloyd F. Pisani W. Marnane Geraldine Boylan A. Temko 18 30 0 28 May 2021
Meta Soft Label Generation for Noisy Labels G. Algan ilkay Ulusoy NoLa 30 38 0 11 Jul 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 36 557 0 30 Jun 2020
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods Daniel Y. Fu Mayee F. Chen Frederic Sala Sarah Hooper Kayvon Fatahalian Christopher Ré OffRL 34 111 0 27 Feb 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 40 104 0 11 Jan 2020
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO Pablo Morales-Álvarez Pablo Ruiz S. Coughlin Rafael Molina Aggelos K. Katsaggelos 21 14 0 05 Nov 2019
Multi-Resolution Weak Supervision for Sequential Data Frederic Sala P. Varma Jason Alan Fries Daniel Y. Fu Shiori Sagawa ... A. Ramamoorthy K. Xiao Kayvon Fatahalian J. Priest Christopher Ré NoLa 22 28 0 21 Oct 2019
Natural Vocabulary Emerges from Free-Form Annotations Jordi Pont-Tuset Michael Gygli V. Ferrari VLM 26 3 0 04 Jun 2019
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks Mingchen Li Mahdi Soltanolkotabi Samet Oymak NoLa 55 351 0 27 Mar 2019
Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion Ryutaro Tanno A. Saeedi S. Sankaranarayanan Daniel C. Alexander N. Silberman NoLa 27 228 0 10 Feb 2019
Learning to quantify emphysema extent: What labels do we need? S. Ørting Jens Petersen L. Thomsen M. Wille Marleen de Bruijne 21 2 0 17 Oct 2018
Direct Uncertainty Prediction for Medical Second Opinions M. Raghu Katy Blumer Rory Sayres Ziad Obermeyer Robert D. Kleinberg S. Mullainathan Jon M. Kleinberg OOD UD 27 136 0 04 Jul 2018
Crowd disagreement about medical images is informative Veronika Cheplygina J. Pluim 22 24 0 21 Jun 2018
Chief complaint classification with recurrent neural networks Scott H. Lee Drew Levin Patrick D. Finley C. Heilig 21 30 0 19 May 2018
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis Veronika Cheplygina Marleen de Bruijne J. Pluim 23 745 0 17 Apr 2018
Fast Dawid-Skene: A Fast Vote Aggregation Scheme for Sentiment Classification Vaibhav Sinha Sukrut Rao V. Balasubramanian 21 28 0 07 Mar 2018
Self-Learning to Detect and Segment Cysts in Lung CT Images without Manual Annotation Ling Zhang Vissagan Gopalakrishnan Le Lu Ronald M. Summers J. Moss Jianhua Yao MedIm 29 38 0 25 Jan 2018
Learning From Noisy Singly-labeled Data A. Khetan Zachary Chase Lipton Anima Anandkumar NoLa 16 160 0 13 Dec 2017
Deep learning from crowds Filipe Rodrigues Francisco Câmara Pereira FedML NoLa 29 256 0 06 Sep 2017
Deep Learning is Robust to Massive Label Noise David Rolnick Andreas Veit Serge J. Belongie Nir Shavit NoLa 36 550 0 30 May 2017