A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning

6 November 2023

Papers citing "A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning"

6 / 6 papers shown

Title
DATA: Multi-Disentanglement based Contrastive Learning for Open-World Semi-Supervised Deepfake Attribution Ming-Hui Liu Xiao-Qian Liu Xin Luo Xin-Shun Xu 51 0 0 07 May 2025
Deep Active Learning in the Open World Tian Xie Jifan Zhang Haoyue Bai R. Nowak VLM 65 0 0 10 Nov 2024
Process Reward Model with Q-Value Rankings W. Li Yixuan Li LRM 45 14 0 15 Oct 2024
HiLo: A Learning Framework for Generalized Category Discovery Robust to Domain Shifts Hongjun Wang S. Vaze Kai Han 61 4 0 08 Aug 2024
Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning Junkai Huang Chaowei Fang Weikai Chen Z. Chai Xiaolin K. Wei Pengxu Wei Liang Lin Guanbin Li OODD 46 63 0 12 Aug 2021
Conditional Gaussian Distribution Learning for Open Set Recognition Xin Sun Zhen Yang Chi Zhang Guohao Peng K. Ling BDL UQCV 139 214 0 19 Mar 2020