6 citations · 6 across the 7 of their papers we have counts for
6 papers · 1 filter
DAPLSR: Data Augmentation Partial Least Squares Regression Model via Manifold Optimization
Haoran Chen, Jiapeng Liu, Jiafan Wang +1
Traditional Partial Least Squares Regression (PLSR) models frequently underperform when handling data characterized by uneven categories. To address the issue, this paper proposes…
Preference Construction: A Bayesian Interactive Preference Elicitation Framework Based on Monte Carlo Tree Search
Yan Wang, Jiapeng Liu, Milosz Kadziński +1
We present a novel preference learning framework to capture participant preferences efficiently within limited interaction rounds. It involves three main contributions. First, we d…
Efficient Generalized Low-Rank Tensor Contextual Bandits
Qianxin Yi, Yiyang Yang, Shaojie Tang +2
In this paper, we aim to build a novel bandits algorithm that is capable of fully harnessing the power of multi-dimensional data and the inherent non-linearity of reward functions…
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…
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…