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20152024
most citedLearning under Concept Drift: A Review

943 citations · 1.2k across the 22 of their papers we have counts for

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19 papers · 1 filter

cs.LG2024

Online Boosting Adaptive Learning under Concept Drift for Multistream Classification

En Yu, Jie Lu, Bin Zhang +1

Multistream classification poses significant challenges due to the necessity for rapid adaptation in dynamic streaming processes with concept drift. Despite the growing research ou…

cs.LG2023

Meta OOD Learning for Continuously Adaptive OOD Detection

Xinheng Wu, Jie Lu, Zhen Fang +1

Out-of-distribution (OOD) detection is crucial to modern deep learning applications by identifying and alerting about the OOD samples that should not be tested or used for making p…

cs.LG2022

Streaming PAC-Bayes Gaussian process regression with a performance guarantee for online decision making

Tianyu Liu, Jie Lu, Zheng Yan +1

As a powerful Bayesian non-parameterized algorithm, the Gaussian process (GP) has performed a significant role in Bayesian optimization and signal processing. GPs have also advance…

cs.LG20214 cited

Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning

Junyu Xuan, Jie Lu, Guangquan Zhang

Transfer learning where the behavior of extracting transferable knowledge from the source domain(s) and reusing this knowledge to target domain has become a research area of great…

cs.LG20212 cited

Learning Bounds for Open-Set Learning

Zhen Fang, Jie Lu, Anjin Liu +2

Traditional supervised learning aims to train a classifier in the closed-set world, where training and test samples share the same label space. In this paper, we target a more chal…

cs.LG20215 cited

PAC-Bayes Bounds for Meta-learning with Data-Dependent Prior

Tianyu Liu, Jie Lu, Zheng Yan +1

By leveraging experience from previous tasks, meta-learning algorithms can achieve effective fast adaptation ability when encountering new tasks. However it is unclear how the gene…