14 citations · 16 across the 5 of their papers we have counts for
5 papers
A New Transformation Approach for Uplift Modeling with Binary Outcome
Kun Li, Liangshu Zhu
Uplift modeling has been used effectively in fields such as marketing and customer retention, to target those customers who are more likely to respond due to the campaign or treatm…
Causal Inference Based Single-branch Ensemble Trees For Uplift Modeling
Fanglan Zheng, Menghan Wang, Kun Li +2
In this manuscript (ms), we propose causal inference based single-branch ensemble trees for uplift modeling, namely CIET. Different from standard classification methods for predict…
LSTM-RPA: A Simple but Effective Long Sequence Prediction Algorithm for Music Popularity Prediction
Kun Li, Meng Li, Yanling Li +1
The big data about music history contains information about time and users' behavior. Researchers could predict the trend of popular songs accurately by analyzing this data. The tr…
A Vertical Federated Learning Method for Interpretable Scorecard and Its Application in Credit Scoring
Fanglan Zheng, Erihe, Kun Li +2
With the success of big data and artificial intelligence in many fields, the applications of big data driven models are expected in financial risk management especially credit scor…
A Federated F-score Based Ensemble Model for Automatic Rule Extraction
Kun Li, Fanglan Zheng, Jiang Tian +1
In this manuscript, we propose a federated F-score based ensemble tree model for automatic rule extraction, namely Fed-FEARE. Under the premise of data privacy protection, Fed-FEAR…