Rethinking Open-World Semi-Supervised Learning: Distribution Mismatch and Inductive Inference

31 May 2024

Papers citing "Rethinking Open-World Semi-Supervised Learning: Distribution Mismatch and Inductive Inference"

6 / 6 papers shown

Title
Temperature Schedules for Self-Supervised Contrastive Methods on Long-Tail Data Anna Kukleva Moritz Bohle Bernt Schiele Hilde Kuehne Christian Rupprecht 29 38 0 23 Mar 2023
Towards Realistic Semi-Supervised Learning Mamshad Nayeem Rizve Navid Kardan M. Shah 34 44 0 05 Jul 2022
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition Haotao Wang Aston Zhang Yi Zhu Shuai Zheng Mu Li Alexander J. Smola Zhangyang Wang OODD 122 48 0 04 Jul 2022
On Non-Random Missing Labels in Semi-Supervised Learning Xinting Hu Yulei Niu C. Miao Xiansheng Hua Hanwang Zhang 14 17 0 29 Jun 2022
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 2021
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 160 25,150 0 09 Jun 2011