Lan-Zhe Guo

According to our database, Lan-Zhe Guo authored at least 27 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Transfer and share: semi-supervised learning from long-tailed data.

Tong Wei, Qian-Yu Liu, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo

Mach. Learn., April, 2024

Open-set learning under covariate shift.

Jie-Jing Shao, Xiaowen Yang, Lan-Zhe Guo

Mach. Learn., April, 2024

Interactive Reweighting for Mitigating Label Quality Issues.

Weikai Yang, Yukai Guo, Jing Wu, Zheng Wang, Lan-Zhe Guo, Yu-Feng Li, Shixia Liu

IEEE Trans. Vis. Comput. Graph., March, 2024

2023

Investigating the Limitation of CLIP Models: The Worst-Performing Categories.

Jie-Jing Shao, Jiang-Xin Shi, Xiaowen Yang, Lan-Zhe Guo, Yu-Feng Li

CoRR, 2023

Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions.

Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yuke Xiang, Yu-Feng Li

Proceedings of the International Conference on Machine Learning, 2023

Identifying Useful Learnwares for Heterogeneous Label Spaces.

Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li, Zhi-Hua Zhou

Proceedings of the International Conference on Machine Learning, 2023

ODS: Test-Time Adaptation in the Presence of Open-World Data Shift.

Zhi Zhou, Lan-Zhe Guo, Lin-Han Jia, Dingchu Zhang, Yu-Feng Li

Proceedings of the International Conference on Machine Learning, 2023

2022

USB: A Unified Semi-supervised Learning Benchmark.

Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang

CoRR, 2022

LAMDA-SSL: Semi-Supervised Learning in Python.

Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li

CoRR, 2022

USB: A Unified Semi-supervised Learning Benchmark for Classification.

Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

LOG: Active Model Adaptation for Label-Efficient OOD Generalization.

Jie-Jing Shao, Lan-Zhe Guo, Xiaowen Yang, Yu-Feng Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust Semi-Supervised Learning when Not All Classes have Labels.

Lan-Zhe Guo, Yi-Ge Zhang, Zhi-Fan Wu, Jie-Jing Shao, Yu-Feng Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding.

Lan-Zhe Guo, Yu-Feng Li

Proceedings of the International Conference on Machine Learning, 2022

2021

Interactive Graph Construction for Graph-Based Semi-Supervised Learning.

Changjian Chen, Zhaowei Wang, Jing Wu, Xiting Wang, Lan-Zhe Guo, Yu-Feng Li, Shixia Liu

IEEE Trans. Vis. Comput. Graph., 2021

Towards Safe Weakly Supervised Learning.

Yu-Feng Li, Lan-Zhe Guo, Zhi-Hua Zhou

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Learning from group supervision: the impact of supervision deficiency on multi-label learning.

Miao Xu, Lan-Zhe Guo

Sci. China Inf. Sci., 2021

STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data.

Zhi Zhou, Lan-Zhe Guo, Zhanzhan Cheng, Yu-Feng Li, Shiliang Pu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment.

Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Qi Zhang, Feng Kuang, Gao-Le Li, Zhang-Xun Liu, Guobin Wu, Nan Ma, Qun (Tracy) Li, Yu-Feng Li

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Weakly Supervised Learning Meets Ride-Sharing User Experience Enhancement.

Lan-Zhe Guo, Feng Kuang, Zhang-Xun Liu, Yu-Feng Li, Nan Ma, Xiao-Hu Qie

CoRR, 2020

RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.

Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data.

Lan-Zhe Guo, Zhenyu Zhang, Yuan Jiang, Yu-Feng Li, Zhi-Hua Zhou

Proceedings of the 37th International Conference on Machine Learning, 2020

IWE-Net: Instance Weight Network for Locating Negative Comments and its application to improve Traffic User Experience.

Lan-Zhe Guo, Feng Kuang, Zhang-Xun Liu, Yu-Feng Li, Nan Ma, Xiao-Hu Qie

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness.

Lan-Zhe Guo, Yu-Feng Li, Ming Li, Jinfeng Yi, Bowen Zhou, Zhi-Hua Zhou

CoRR, 2019

Robust Semi-supervised Representation Learning for Graph-Structured Data.

Lan-Zhe Guo, Tao Han, Yu-Feng Li

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

2018

Learning safe multi-label prediction for weakly labeled data.

Tong Wei, Lan-Zhe Guo, Yu-Feng Li, Wei Gao

Mach. Learn., 2018

Large Margin Graph Construction for Semi-Supervised Learning.

Lan-Zhe Guo, Shao-Bo Wang, Yu-Feng Li

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

A General Formulation for Safely Exploiting Weakly Supervised Data.

Lan-Zhe Guo, Yu-Feng Li

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018