Understanding Difficulty-based Sample Weighting with a Universal Difficulty Measure

12 January 2023

Papers citing "Understanding Difficulty-based Sample Weighting with a Universal Difficulty Measure"

22 / 22 papers shown

Title
Which Samples Should be Learned First: Easy or Hard? Xiaoling Zhou Ou Wu 58 17 0 11 Oct 2021
Understanding the role of importance weighting for deep learning Da Xu Yuting Ye Chuanwei Ruan FAtt 69 44 0 28 Mar 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 343 1,922 0 12 Nov 2020
Geometry-aware Instance-reweighted Adversarial Training Jingfeng Zhang Jianing Zhu Gang Niu Bo Han Masashi Sugiyama Mohan Kankanhalli AAML 53 278 0 05 Oct 2020
Asymmetric Loss For Multi-Label Classification Emanuel Ben-Baruch T. Ridnik Nadav Zamir Asaf Noy Itamar Friedman M. Protter Lihi Zelnik-Manor 86 541 0 29 Sep 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics Swabha Swayamdipta Roy Schwartz Nicholas Lourie Yizhong Wang Hannaneh Hajishirzi Noah A. Smith Yejin Choi 115 448 0 22 Sep 2020
Estimating Example Difficulty Using Variance of Gradients Chirag Agarwal Daniel D'souza Sara Hooker 251 110 0 26 Aug 2020
Which Strategies Matter for Noisy Label Classification? Insight into Loss and Uncertainty Wonyoung Shin Jung-Woo Ha Shengzhe Li Yongwoo Cho Hoyean Song Sunyoung Kwon NoLa 45 9 0 14 Aug 2020
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks Zitong Yang Yaodong Yu Chong You Jacob Steinhardt Yi-An Ma 67 185 0 26 Feb 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat Francis R. Bach MLT 124 339 0 11 Feb 2020
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 87 335 0 13 Jun 2019
Class-Balanced Loss Based on Effective Number of Samples Huayu Chen Menglin Jia Nayeon Lee Yang Song Serge J. Belongie 202 2,281 0 16 Jan 2019
What is the Effect of Importance Weighting in Deep Learning? Jonathon Byrd Zachary Chase Lipton 96 465 0 08 Dec 2018
Quantifying Uncertainties in Natural Language Processing Tasks Yijun Xiao William Yang Wang UQCV BDL 77 151 0 18 Nov 2018
Gradient Harmonized Single-stage Detector Buyu Li Yu Liu Xiaogang Wang ObjD 53 529 0 13 Nov 2018
Large Margin Deep Networks for Classification Gamaleldin F. Elsayed Dilip Krishnan H. Mobahi Kevin Regan Samy Bengio MQ 56 284 0 15 Mar 2018
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 158 921 0 27 Oct 2017
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples Haw-Shiuan Chang Erik Learned-Miller Andrew McCallum 75 353 0 24 Apr 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 359 4,709 0 15 Mar 2017
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Cost Sensitive Learning of Deep Feature Representations from Imbalanced Data Salman H. Khan Munawar Hayat Bennamoun Ferdous Sohel R. Togneri 74 882 0 14 Aug 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 829 9,318 0 06 Jun 2015