2025 "semi-supervised learning" Papers
15 papers found
CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution
Yunju Cho, Jay-Yoon Lee
ICLR 2025oral
1
citations
CustomKD: Customizing Large Vision Foundation for Edge Model Improvement via Knowledge Distillation
Jungsoo Lee, Debasmit Das, Munawar Hayat et al.
CVPR 2025posterarXiv:2503.18244
3
citations
DyCON: Dynamic Uncertainty-aware Consistency and Contrastive Learning for Semi-supervised Medical Image Segmentation
Maregu Assefa, Muzammal Naseer, IYYAKUTTI IYAPPAN GANAPATHI et al.
CVPR 2025posterarXiv:2504.04566
6
citations
Functional Virtual Adversarial Training for Semi-Supervised Time Series Classification
Qingyi Pan, Yicheng Li
NeurIPS 2025oral
Joint Diffusion Models in Continual Learning
Paweł Skierś, Kamil Deja
ICCV 2025posterarXiv:2411.08224
3
citations
Keep It on a Leash: Controllable Pseudo-label Generation Towards Realistic Long-Tailed Semi-Supervised Learning
Yaxin Hou, Bo Han, Yuheng Jia et al.
NeurIPS 2025posterarXiv:2510.03993
Prediction-Powered Semi-Supervised Learning with Online Power Tuning
Noa Shoham, Ron Dorfman, Shalev Shaer et al.
NeurIPS 2025posterarXiv:2510.22586
1
citations
SemiDAViL: Semi-supervised Domain Adaptation with Vision-Language Guidance for Semantic Segmentation
Hritam Basak, Zhaozheng Yin
CVPR 2025posterarXiv:2504.06389
1
citations
Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency
Kai Gan, Bo Ye, Min-Ling Zhang et al.
ICLR 2025poster
3
citations
Semi-supervised Vertex Hunting, with Applications in Network and Text Analysis
Yicong Jiang, Zheng Tracy Ke
NeurIPS 2025posterarXiv:2510.22526
Steady Progress Beats Stagnation: Mutual Aid of Foundation and Conventional Models in Mixed Domain Semi-Supervised Medical Image Segmentation
Qinghe Ma, Jian Zhang, Zekun Li et al.
CVPR 2025posterarXiv:2503.16997
4
citations
STiL: Semi-supervised Tabular-Image Learning for Comprehensive Task-Relevant Information Exploration in Multimodal Classification
Siyi Du, Xinzhe Luo, Declan ORegan et al.
CVPR 2025posterarXiv:2503.06277
3
citations
Theoretical Insights into In-context Learning with Unlabeled Data
Yingcong Li, Xiangyu Chang, Muti Kara et al.
NeurIPS 2025poster
Towards Scalable Topological Regularizers
Wong Hiu-Tung, Darrick Lee, Hong Yan
ICLR 2025posterarXiv:2501.14641
1
citations
Uncertainty-Informed Meta Pseudo Labeling for Surrogate Modeling with Limited Labeled Data
Xingyu Ren, Pengwei Liu, Pengkai Wang et al.
NeurIPS 2025poster