activity
20152022
most citedLearning under Concept Drift: A Review

943 citations · 1.2k across the 17 of their papers we have counts for

collaborators

24 papers

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…

stat.ML2021

Deep Bayesian Estimation for Dynamic Treatment Regimes with a Long Follow-up Time

Adi Lin, Jie Lu, Junyu Xuan +2

Causal effect estimation for dynamic treatment regimes (DTRs) contributes to sequential decision making. However, censoring and time-dependent confounding under DTRs are challengin…

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.AI2021

Automatic Learning to Detect Concept Drift

Hang Yu, Tianyu Liu, Jie Lu +1

Many methods have been proposed to detect concept drift, i.e., the change in the distribution of streaming data, due to concept drift causes a decrease in the prediction accuracy o…

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…