Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2002.10319
Cited By
v1
v2 (latest)
Self-Adaptive Training: beyond Empirical Risk Minimization
Neural Information Processing Systems (NeurIPS), 2020
24 February 2020
Lang Huang
Chaoning Zhang
Hongyang R. Zhang
NoLa
Re-assign community
ArXiv (abs)
PDF
HTML
Github (128★)
Papers citing
"Self-Adaptive Training: beyond Empirical Risk Minimization"
50 / 122 papers shown
What Does It Take to Build a Performant Selective Classifier?
Stephan Rabanser
Nicolas Papernot
274
2
0
23 Oct 2025
Pseudo-D: Informing Multi-View Uncertainty Estimation with Calibrated Neural Training Dynamics
A. Gu
Michael Y. Tsang
H. Vaseli
Purang Abolmaesumi
T. Tsang
UQCV
173
0
0
15 Sep 2025
Theoretical Analysis of Relative Errors in Gradient Computations for Adversarial Attacks with CE Loss
Yunrui Yu
Hang Su
Cheng-zhong Xu
Zhizhong Su
Jun Zhu
224
1
0
30 Jul 2025
Suitability Filter: A Statistical Framework for Classifier Evaluation in Real-World Deployment Settings
Angéline Pouget
Mohammad Yaghini
Stephan Rabanser
Nicolas Papernot
258
2
0
28 May 2025
One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP
Binyan Xu
Xilin Dai
Di Tang
Kehuan Zhang
AAML
366
6
0
26 May 2025
Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
Alvin Heng
Harold Soh
409
1
0
21 May 2025
ATM-Net: Anatomy-Aware Text-Guided Multi-Modal Fusion for Fine-Grained Lumbar Spine Segmentation
Sheng Lian
Dengfeng Pan
Jianlong Cai
Guang-Yong Chen
Zhun Zhong
Shaozi Li
Shen Zhao
Shuo Li
341
4
0
04 Apr 2025
Interpretable and Fair Mechanisms for Abstaining Classifiers
Daphne Lenders
Andrea Pugnana
Roberto Pellungrini
Toon Calders
D. Pedreschi
F. Giannotti
FaML
372
2
0
24 Mar 2025
LiDAR Remote Sensing Meets Weak Supervision: Concepts, Methods, and Perspectives
Yuan Gao
Shaobo Xia
Peijie Wang
Xiaohuan Xi
Sheng Nie
Cheng-Xiang Wang
493
5
0
24 Mar 2025
Fast Adversarial Training against Sparse Attacks Requires Loss Smoothing
Xuyang Zhong
Yixiao Huang
Chen Liu
AAML
472
1
0
28 Feb 2025
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
Neural Information Processing Systems (NeurIPS), 2025
C. Kim
Sangwoo Moon
Jihwan Moon
Dongyeon Woo
Gunhee Kim
NoLa
475
1
0
25 Feb 2025
Democratic Training Against Universal Adversarial Perturbations
International Conference on Learning Representations (ICLR), 2025
Bing-Jie Sun
Jun Sun
Wei Zhao
AAML
300
1
0
08 Feb 2025
Open set label noise learning with robust sample selection and margin-guided module
Knowledge-Based Systems (KBS), 2025
Yuandi Zhao
Qianxi Xia
Yang Sun
Zhijie Wen
Liyan Ma
Shihui Ying
NoLa
367
5
0
08 Jan 2025
Bayesian uncertainty-aware deep learning with noisy labels: Tackling annotation ambiguity in EEG seizure detection
Deeksha M Shama
Archana Venkataraman
NoLa
389
1
0
17 Oct 2024
Robust Network Learning via Inverse Scale Variational Sparsification
Zhiling Zhou
Zirui Liu
Chengming Xu
Yanwei Fu
Xinwei Sun
AAML
310
0
0
27 Sep 2024
Refining Corpora from a Model Calibration Perspective for Chinese Spelling Correction
Dingyao Yu
Yang An
Wei Ye
Xiongfeng Xiao
Shaoguang Mao
Tao Ge
Shikun Zhang
282
1
0
22 Jul 2024
Foster Adaptivity and Balance in Learning with Noisy Labels
Mengmeng Sheng
Zeren Sun
Tao Chen
Shuchao Pang
Yucheng Wang
Yazhou Yao
270
19
0
03 Jul 2024
DataFreeShield: Defending Adversarial Attacks without Training Data
Hyeyoon Lee
Kanghyun Choi
Dain Kwon
Sunjong Park
Mayoore S. Jaiswal
Noseong Park
Jonghyun Choi
Jinho Lee
307
1
0
21 Jun 2024
Beyond the Norms: Detecting Prediction Errors in Regression Models
A. Altieri
Marco Romanelli
Georg Pichler
F. Alberge
Pablo Piantanida
451
1
0
11 Jun 2024
Confidence-aware Contrastive Learning for Selective Classification
International Conference on Machine Learning (ICML), 2024
Yu-Chang Wu
Shen-Huan Lyu
Haopu Shang
Xiangyu Wang
Chao Qian
246
6
0
07 Jun 2024
A Causal Framework for Evaluating Deferring Systems
Filippo Palomba
Andrea Pugnana
Jose M. Alvarez
Salvatore Ruggieri
CML
510
11
0
29 May 2024
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference
Jiayi Huang
Sangwoo Park
Osvaldo Simeone
698
7
0
17 Apr 2024
On adversarial training and the 1 Nearest Neighbor classifier
Amir Hagai
Yair Weiss
AAML
387
0
0
09 Apr 2024
Selective Temporal Knowledge Graph Reasoning
International Conference on Language Resources and Evaluation (LREC), 2024
Zhongni Hou
Xiaolong Jin
Zixuan Li
Long Bai
Jiafeng Guo
Xueqi Cheng
343
0
0
02 Apr 2024
Group Benefits Instances Selection for Data Purification
Zhenhuang Cai
Chuanyi Zhang
Dan Huang
Yuanbo Chen
Xiuyun Guan
Yazhou Yao
NoLa
314
0
0
23 Mar 2024
REPAIR: Rank Correlation and Noisy Pair Half-replacing with Memory for Noisy Correspondence
IEEE transactions on multimedia (IEEE TMM), 2024
Ruochen Zheng
Jiahao Hong
Changxin Gao
Nong Sang
201
3
0
13 Mar 2024
PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive Representation Learning
Xiaoyu Liu
Beitong Zhou
Cheng Cheng
282
11
0
27 Feb 2024
Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection
Huafeng Liu
Mengmeng Sheng
Zeren Sun
Yazhou Yao
Xian-Sheng Hua
Mengqi Li
NoLa
251
20
0
17 Feb 2024
Mitigating Feature Gap for Adversarial Robustness by Feature Disentanglement
Nuoyan Zhou
Dawei Zhou
Decheng Liu
Xinbo Gao
Nannan Wang
AAML
272
0
0
26 Jan 2024
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
AAAI Conference on Artificial Intelligence (AAAI), 2024
Chen-Chen Zong
Ye-Wen Wang
Ming-Kun Xie
Sheng-Jun Huang
272
15
0
13 Jan 2024
Learning with Noisy Labels: Interconnection of Two Expectation-Maximizations
Heewon Kim
Hyun Sung Chang
Kiho Cho
Jaeyun Lee
Bohyung Han
NoLa
202
4
0
09 Jan 2024
Sample selection with noise rate estimation in noise learning of medical image analysis
Maolin Li
G. Tarroni
OOD
317
0
0
23 Dec 2023
Adaptive Integration of Partial Label Learning and Negative Learning for Enhanced Noisy Label Learning
AAAI Conference on Artificial Intelligence (AAAI), 2023
Mengmeng Sheng
Zeren Sun
Zhenhuang Cai
Tao Chen
Yichao Zhou
Yazhou Yao
258
39
0
15 Dec 2023
Understanding the Role of Optimization in Double Descent
Chris Yuhao Liu
Jeffrey Flanigan
307
0
0
06 Dec 2023
Model Agnostic Explainable Selective Regression via Uncertainty Estimation
Andrea Pugnana
Carlos Mougan
Dan Saattrup Nielsen
247
0
0
15 Nov 2023
Resist Label Noise with PGM for Graph Neural Networks
Qingqing Ge
Jianxiang Yu
Zeyuan Zhao
Xiang Li
NoLa
AAML
293
0
0
03 Nov 2023
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
Knowledge Discovery and Data Mining (KDD), 2023
Yao Cheng
Caihua Shan
Yifei Shen
Xiang Li
Siqiang Luo
Dongsheng Li
389
12
0
25 Oct 2023
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks
International Conference on Learning Representations (ICLR), 2023
Yue Cao
Tianlin Li
Xiaofeng Cao
Ivor Tsang
Yang Liu
Qing Guo
AAML
309
4
0
18 Oct 2023
Enhancing Robust Representation in Adversarial Training: Alignment and Exclusion Criteria
Nuoyan Zhou
Nannan Wang
Decheng Liu
Dawei Zhou
Xinbo Gao
AAML
316
2
0
05 Oct 2023
Learning to Abstain From Uninformative Data
Yikai Zhang
Songzhu Zheng
M. Dalirrooyfard
Pengxiang Wu
Anderson Schneider
Anant Raj
Yuriy Nevmyvaka
Chao Chen
246
2
0
25 Sep 2023
Outlier Robust Adversarial Training
Asian Conference on Machine Learning (ACML), 2023
Shu Hu
Zhenhuan Yang
X. Wang
Yiming Ying
Siwei Lyu
AAML
261
10
0
10 Sep 2023
A Noisy-Label-Learning Formulation for Immune Repertoire Classification and Disease-Associated Immune Receptor Sequence Identification
International Joint Conference on Artificial Intelligence (IJCAI), 2023
Mingcai Chen
Yu Zhao
Zhonghuang Wang
Bing He
Jianhua Yao
216
4
0
29 Jul 2023
Omnipotent Adversarial Training in the Wild
Guanlin Li
Kangjie Chen
Yuan Xu
Han Qiu
Tianwei Zhang
359
0
0
14 Jul 2023
Alleviating the Effect of Data Imbalance on Adversarial Training
Guanlin Li
Guowen Xu
Tianwei Zhang
318
4
0
14 Jul 2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World
Network and Distributed System Security Symposium (NDSS), 2023
Weiran Lin
Keane Lucas
Neo Eyal
Lujo Bauer
Michael K. Reiter
Mahmood Sharif
OOD
AAML
315
1
0
29 Jun 2023
Revisiting and Advancing Adversarial Training Through A Simple Baseline
Hong Liu
AAML
276
0
0
13 Jun 2023
Conservative Prediction via Data-Driven Confidence Minimization
Caroline Choi
Fahim Tajwar
Yoonho Lee
Huaxiu Yao
Ananya Kumar
Chelsea Finn
245
7
0
08 Jun 2023
Training Private Models That Know What They Don't Know
Neural Information Processing Systems (NeurIPS), 2023
Stephan Rabanser
Anvith Thudi
Abhradeep Thakurta
Krishnamurthy Dvijotham
Nicolas Papernot
259
10
0
28 May 2023
How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
L. F. P. Cattelan
Danilo Silva
UQCV
520
9
0
24 May 2023
Unsupervised Anomaly Detection with Rejection
Neural Information Processing Systems (NeurIPS), 2023
Lorenzo Perini
Jesse Davis
283
13
0
22 May 2023
1
2
3
Next
Page 1 of 3