Are Labels Always Necessary for Classifier Accuracy Evaluation?

6 July 2020

Liang Zheng

Papers citing "Are Labels Always Necessary for Classifier Accuracy Evaluation?"

30 / 30 papers shown

Title
Supervised Models Can Generalize Also When Trained on Random Labels Oskar Allerbo Thomas B. Schön OOD SSL 42 0 0 16 May 2025
BackMix: Regularizing Open Set Recognition by Removing Underlying Fore-Background Priors Yu Wang Junxian Mu Hongzhi Huang Qilong Wang Pengfei Zhu Q. Hu 60 0 0 22 Mar 2025
Early Stopping Against Label Noise Without Validation Data Suqin Yuan Lei Feng Tongliang Liu NoLa 107 18 0 11 Feb 2025
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions? Weijie Tu Weijian Deng Liang Zheng Tom Gedeon 53 0 0 14 Jun 2024
Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift Renchunzi Xie Ambroise Odonnat Vasilii Feofanov I. Redko Jianfeng Zhang Bo An UQCV 80 1 0 17 Jan 2024
Estimating Model Performance Under Covariate Shift Without Labels Jakub Bialek W. Kuberski Nikolaos Perrakis Albert Bifet 44 2 0 16 Jan 2024
MetaDefa: Meta-learning based on Domain Enhancement and Feature Alignment for Single Domain Generalization Can Sun Hao Zheng Zhigang Hu Liu Yang Meiguang Zheng Bo Xu 21 0 0 27 Nov 2023
Anchor Points: Benchmarking Models with Much Fewer Examples Rajan Vivek Kawin Ethayarajh Diyi Yang Douwe Kiela ALM 34 22 0 14 Sep 2023
Validation of the Practicability of Logical Assessment Formula for Evaluations with Inaccurate Ground-Truth Labels Yongquan Yang Hong Bu 40 0 0 06 Jul 2023
A Bag-of-Prototypes Representation for Dataset-Level Applications Wei-Chih Tu Weijian Deng Tom Gedeon Liang Zheng 49 9 0 23 Mar 2023
Demystifying Disagreement-on-the-Line in High Dimensions Dong-Hwan Lee Behrad Moniri Xinmeng Huang Yan Sun Hamed Hassani 27 8 0 31 Jan 2023
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions Lingjiao Chen Zhihua Jin Sabri Eyuboglu Christopher Ré Matei A. Zaharia James Zou 58 9 0 18 Sep 2022
What can we Learn by Predicting Accuracy? Olivier Risser-Maroix Benjamin Chamand 37 4 0 02 Aug 2022
Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores Zeju Li Konstantinos Kamnitsas Mobarakol Islam Chen Chen Ben Glocker 30 9 0 20 Jul 2022
On the Strong Correlation Between Model Invariance and Generalization Weijian Deng Stephen Gould Liang Zheng OOD 37 16 0 14 Jul 2022
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization Hao Sun B. V. Breugel Jonathan Crabbé Nabeel Seedat M. Schaar 37 4 0 11 Jul 2022
Firenze: Model Evaluation Using Weak Signals Bhavna Soman A. Torkamani Michael J. Morais Jeffrey Bickford Baris Coskun 44 2 0 02 Jul 2022
Performance Prediction Under Dataset Shift Simona Maggio Victor Bouvier L. Dreyfus-Schmidt OOD AI4TS 21 2 0 21 Jun 2022
Attribute Descent: Simulating Object-Centric Datasets on the Content Level and Beyond Yue Yao Liang Zheng Xiaodong Yang Milind Napthade Tom Gedeon 33 17 0 28 Feb 2022
Deconstructing Distributions: A Pointwise Framework of Learning Gal Kaplun Nikhil Ghosh Saurabh Garg Boaz Barak Preetum Nakkiran OOD 38 21 0 20 Feb 2022
Predicting Out-of-Distribution Error with the Projection Norm Yaodong Yu Zitong Yang Alexander Wei Yi Ma Jacob Steinhardt OODD 25 43 0 11 Feb 2022
Label-Free Model Evaluation with Semi-Structured Dataset Representations Xiaoxiao Sun Yunzhong Hou Hongdong Li Liang Zheng 27 11 0 01 Dec 2021
One to Transfer All: A Universal Transfer Framework for Vision Foundation Model with Few Data Yujie Wang Junqin Huang Mengya Gao Yichao Wu Zhen-fei Yin Ding Liang Junjie Yan 14 0 0 24 Nov 2021
Logical Assessment Formula and Its Principles for Evaluations with Inaccurate Ground-Truth Labels Yongquan Yang 41 3 0 22 Oct 2021
A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels R. Joyce Edward Raff Charles K. Nicholas 51 16 0 23 Sep 2021
Predicting with Confidence on Unseen Distributions Devin Guillory Vaishaal Shankar Sayna Ebrahimi Trevor Darrell Ludwig Schmidt UQCV OOD 30 117 0 07 Jul 2021
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles Jiefeng Chen Frederick Liu Besim Avci Xi Wu Yingyu Liang S. Jha 32 61 0 29 Jun 2021
Towards Distraction-Robust Active Visual Tracking Fangwei Zhong Peng Sun Wenhan Luo Tingyun Yan Yizhou Wang AAML 30 33 0 18 Jun 2021
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? Weijian Deng Stephen Gould Liang Zheng 39 63 0 10 Jun 2021
Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation Binghao Liu Yao Ding Jianbin Jiao Xiangyang Ji QiXiang Ye 29 47 0 01 Jun 2021