Machine and deep learning performance in out-of-distribution regressions

被引：0
|
作者：
Shmuel, Assaf [1 ]
Glickman, Oren [1 ]
Lazebnik, Teddy [2 ]
机构：
[1] Department of Computer Science, Bar Ilan University, Ramat Gan, Israel
[2] Department of Cancer Biology, Cancer Institute, University College London, London, United Kingdom
来源：
Machine Learning: Science and Technology | 2024年 / 5卷 / 04期
关键词：
Compendex;
D O I：
10.1088/2632-2153/ada221
中图分类号：
学科分类号：
摘要：
Adversarial machine learning
引用
收藏
相关论文
共 50 条
  • [41] Sample-free white-box out-of-distribution detection for deep learning
    Begon, Jean-Michel
    Geurts, Pierre
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 3285 - 3294
  • [42] CausPref: Causal Preference Learning for Out-of-Distribution Recommendation
    He, Yue
    Wang, Zimu
    Cui, Peng
    Zou, Hao
    Zhang, Yafeng
    Cui, Qiang
    Jiang, Yong
    PROCEEDINGS OF THE ACM WEB CONFERENCE 2022 (WWW'22), 2022, : 410 - 421
  • [43] Model Agnostic Sample Reweighting for Out-of-Distribution Learning
    Zhou, Xiao
    Lin, Yong
    Pi, Renjie
    Zhang, Weizhong
    Xu, Renzhe
    Cui, Peng
    Zhang, Tong
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162, 2022,
  • [44] Understanding and Improving Feature Learning for Out-of-Distribution Generalization
    Chen, Yongqiang
    Huang, Wei
    Zhou, Kaiwen
    Bian, Yatao
    Han, Bo
    Cheng, James
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 36 (NEURIPS 2023), 2023,
  • [45] Fooling machine learning models: a novel out-of-distribution attack through generative adversarial networks
    Hu, Hailong
    Pang, Jun
    APPLIED INTELLIGENCE, 2025, 55 (05)
  • [46] Generalizing Reward Modeling for Out-of-Distribution Preference Learning
    Jia, Chen
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES: RESEARCH TRACK, PT V, ECML PKDD 2024, 2024, 14945 : 107 - 124
  • [47] Learning Invariant Graph Representations for Out-of-Distribution Generalization
    Li, Haoyang
    Zhang, Ziwei
    Wang, Xin
    Zhu, Wenwu
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35 (NEURIPS 2022), 2022,
  • [48] Learning Causal Semantic Representation for Out-of-Distribution Prediction
    Liu, Chang
    Sun, Xinwei
    Wang, Jindong
    Tang, Haoyue
    Li, Tao
    Qin, Tao
    Chen, Wei
    Liu, Tie-Yan
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 34 (NEURIPS 2021), 2021, 34
  • [49] Learning Substructure Invariance for Out-of-Distribution Molecular Representations
    Yang, Nianzu
    Zeng, Kaipeng
    Wu, Qitian
    Jia, Xiaosong
    Yan, Junchi
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35 (NEURIPS 2022), 2022,
  • [50] Harnessing Error Patterns to Estimate Out-of-Distribution Performance
    Bonnier, Thomas
    Bosch, Benjamin
    MACHINE LEARNING AND PRINCIPLES AND PRACTICE OF KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2023, PT IV, 2025, 2136 : 381 - 389
12345