Self-Adaptive Training: beyond Empirical Risk Minimization

24 February 2020

Papers citing "Self-Adaptive Training: beyond Empirical Risk Minimization"

31 / 31 papers shown

Title
Interpretable and Fair Mechanisms for Abstaining Classifiers Daphne Lenders Andrea Pugnana Roberto Pellungrini Toon Calders D. Pedreschi F. Giannotti FaML 89 1 0 24 Mar 2025
Sample Selection via Contrastive Fragmentation for Noisy Label Regression C. Kim Sangwoo Moon Jihwan Moon Dongyeon Woo Gunhee Kim NoLa 52 0 0 25 Feb 2025
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference Jiayi Huang Sangwoo Park Osvaldo Simeone 94 2 0 03 Jan 2025
A Causal Framework for Evaluating Deferring Systems Filippo Palomba Andrea Pugnana Jose M. Alvarez Salvatore Ruggieri CML 46 1 0 29 May 2024
Learning with Noisy Labels: Interconnection of Two Expectation-Maximizations Heewon Kim Hyun Sung Chang Kiho Cho Jaeyun Lee Bohyung Han NoLa 21 2 0 09 Jan 2024
Learning to Abstain From Uninformative Data Yikai Zhang Songzhu Zheng M. Dalirrooyfard Pengxiang Wu Anderson Schneider Anant Raj Yuriy Nevmyvaka Chao Chen 16 2 0 25 Sep 2023
Omnipotent Adversarial Training in the Wild Guanlin Li Kangjie Chen Yuan Xu Han Qiu Tianwei Zhang 16 0 0 14 Jul 2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World Weiran Lin Keane Lucas Neo Eyal Lujo Bauer Michael K. Reiter Mahmood Sharif OOD AAML 22 1 0 29 Jun 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 34 49 0 18 May 2023
CAT:Collaborative Adversarial Training Xingbin Liu Huafeng Kuang Xianming Lin Yongjian Wu Rongrong Ji AAML 17 4 0 27 Mar 2023
AUC-based Selective Classification Andrea Pugnana Salvatore Ruggieri 21 9 0 19 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 28 24 0 12 Oct 2022
CrowdChecked: Detecting Previously Fact-Checked Claims in Social Media Momchil Hardalov Anton Chernyavskiy Ivan Koychev Dmitry Ilvovsky Preslav Nakov HAI 27 15 0 10 Oct 2022
Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance Bahjat Kawar Roy Ganz Michael Elad DiffM 21 38 0 18 Aug 2022
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang Li Shen Jian Yang Chen Gong NoLa 21 5 0 27 Jun 2022
Selective Classification Via Neural Network Training Dynamics Stephan Rabanser Anvith Thudi Kimia Hamidieh Adam Dziedzic Nicolas Papernot 18 21 0 26 May 2022
CE-based white-box adversarial attacks will not work using super-fitting Youhuan Yang Lei Sun Leyu Dai Song Guo Xiuqing Mao Xiaoqin Wang Bayi Xu AAML 24 0 0 04 May 2022
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning Sangmook Kim Wonyoung Shin Soohyuk Jang Hwanjun Song Se-Young Yun 29 2 0 03 May 2022
Adversarial Robustness through the Lens of Convolutional Filters Paul Gavrikov J. Keuper 30 15 0 05 Apr 2022
Better Supervisory Signals by Observing Learning Paths Yi Ren Shangmin Guo Danica J. Sutherland 25 21 0 04 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 31 42 0 27 Feb 2022
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 15 13 0 14 Dec 2021
Data Augmentation Can Improve Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 17 269 0 09 Nov 2021
Improved Regularization and Robustness for Fine-tuning in Neural Networks Dongyue Li Hongyang R. Zhang NoLa 49 54 0 08 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks Maksym Yatsura J. H. Metzen Matthias Hein OOD 24 14 0 02 Nov 2021
Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification Jinghan Sun Dong Wei Kai Ma Liansheng Wang Yefeng Zheng 14 8 0 09 Oct 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 15 23 0 12 Jun 2021
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks Leo Schwinn René Raab A. Nguyen Dario Zanca Bjoern M. Eskofier AAML 14 58 0 21 May 2021
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 25 44 0 19 Apr 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 25 268 0 02 Mar 2021
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 323 0 07 Oct 2020