Lan-Zhe Guo

Orcid: 0000-0001-8965-1288

According to our database1, Lan-Zhe Guo authored at least 34 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Transfer and share: semi-supervised learning from long-tailed data.
Mach. Learn., April, 2024

Open-set learning under covariate shift.
Mach. Learn., April, 2024

Interactive Reweighting for Mitigating Label Quality Issues.
IEEE Trans. Vis. Comput. Graph., March, 2024

Robustness Assessment of Mathematical Reasoning in the Presence of Missing and Contradictory Conditions.
CoRR, 2024

LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model.
CoRR, 2024

DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection.
CoRR, 2024

LAMDA-SSL: a comprehensive semi-supervised learning toolkit.
Sci. China Inf. Sci., 2024

Offline Imitation Learning with Model-based Reverse Augmentation.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Investigating the Limitation of CLIP Models: The Worst-Performing Categories.
CoRR, 2023

Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions.
Proceedings of the International Conference on Machine Learning, 2023

Identifying Useful Learnwares for Heterogeneous Label Spaces.
Proceedings of the International Conference on Machine Learning, 2023

ODS: Test-Time Adaptation in the Presence of Open-World Data Shift.
Proceedings of the International Conference on Machine Learning, 2023

2022
USB: A Unified Semi-supervised Learning Benchmark.
CoRR, 2022

LAMDA-SSL: Semi-Supervised Learning in Python.
CoRR, 2022

USB: A Unified Semi-supervised Learning Benchmark for Classification.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

2021
Interactive Graph Construction for Graph-Based Semi-Supervised Learning.
IEEE Trans. Vis. Comput. Graph., 2021

Towards Safe Weakly Supervised Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Learning from group supervision: the impact of supervision deficiency on multi-label learning.
Sci. China Inf. Sci., 2021

STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data.
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.
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.
CoRR, 2020

RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.
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.
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.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness.
CoRR, 2019

Robust Semi-supervised Representation Learning for Graph-Structured Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

2018
Learning safe multi-label prediction for weakly labeled data.
Mach. Learn., 2018

Large Margin Graph Construction for Semi-Supervised Learning.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

A General Formulation for Safely Exploiting Weakly Supervised Data.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018


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