7 citations · 25 across the 7 of their papers we have counts for
7 papers
Efficient Fraud Detection Using Deep Boosting Decision Trees
Biao Xu, Yao Wang, Xiuwu Liao +1
Fraud detection is to identify, monitor, and prevent potentially fraudulent activities from complex data. The recent development and success in AI, especially machine learning, pro…
An Improved Frequent Directions Algorithm for Low-Rank Approximation via Block Krylov Iteration
Chenhao Wang, Qianxin Yi, Xiuwu Liao +1
Frequent Directions, as a deterministic matrix sketching technique, has been proposed for tackling low-rank approximation problems. This method has a high degree of accuracy and pr…
An interpretable neural network model through piecewise linear approximation
Mengzhuo Guo, Qingpeng Zhang, Xiuwu Liao +1
Most existing interpretable methods explain a black-box model in a post-hoc manner, which uses simpler models or data analysis techniques to interpret the predictions after the mod…
Explainable Ordinal Factorization Model: Deciphering the Effects of Attributes by Piece-wise Linear Approximation
Mengzhuo Guo, Zhongzhi Xu, Qingpeng Zhang +2
Ordinal regression predicts the objects' labels that exhibit a natural ordering, which is important to many managerial problems such as credit scoring and clinical diagnosis. In th…
A preference learning framework for multiple criteria sorting with diverse additive value models and valued assignment examples
Jiapeng Liu, Milosz Kadzinski, Xiuwu Liao +2
We present a preference learning framework for multiple criteria sorting. We consider sorting procedures applying an additive value model with diverse types of marginal value funct…
A hybrid machine learning framework for analyzing human decision making through learning preferences
Mengzhuo Guo, Qingpeng Zhang, Xiuwu Liao +2
Machine learning has recently been widely adopted to address the managerial decision making problems, in which the decision maker needs to be able to interpret the contributions of…
Data-driven preference learning methods for value-driven multiple criteria sorting with interacting criteria
Jiapeng Liu, Milosz Kadzinski, Xiuwu Liao +1
The learning of predictive models for data-driven decision support has been a prevalent topic in many fields. However, construction of models that would capture interactions among…