107 citations · 276 across the 10 of their papers we have counts for
10 papers
Effort-Centric Fairness in Lending Decisions
Shiqi Fang, Zexun Chen, Jake Ansell
Algorithmic credit scoring must satisfy fairness and explanation requirements, yet prevailing predictive-parity criteria assess only outcomes at the decision point. They can theref…
When is multivariate kriging worthwhile? Design geometry, parameter sharing and response coupling under heterotopic sampling
Zexun Chen, Jun Fan, Kuo Wang
We investigate when multivariate kriging improves on separate prediction, using separable multi-output Gaussian processes as the principal theoretical benchmark. We introduce direc…
Bridging Structured Knowledge and Data: A Unified Framework with Finance Applications
Yi Cao, Zexun Chen, Lin William Cong +1
We develop Structured-Knowledge-Informed Neural Networks (SKINNs), a unified estimation framework that embeds theoretical, simulated, previously learned, or cross-domain insights a…
Peer-induced Fairness: A Causal Approach for Algorithmic Fairness Auditing
Shiqi Fang, Zexun Chen, Jake Ansell
With the European Union's Artificial Intelligence Act taking effect on 1 August 2024, high-risk AI applications must adhere to stringent transparency and fairness standards. This p…
Dynamic predictability and spatio-temporal contexts in human mobility
Bibandhan Poudyal, Diogo Pacheco, Marcos Oliveira +4
Human travelling behaviours are markedly regular, to a large extent, predictable, and mostly driven by biological necessities (\eg sleeping, eating) and social constructs (\eg scho…
Contrasting social and non-social sources of predictability in human mobility
Zexun Chen, Sean Kelty, Brooke Foucault Welles +3
Social structures influence a variety of human behaviors including mobility patterns, but the extent to which one individual's movements can predict another's remains an open quest…
Remarks on multivariate Gaussian Process
Zexun Chen, Jun Fan, Kuo Wang
Gaussian processes occupy one of the leading places in modern statistics and probability theory due to their importance and a wealth of strong results. The common use of Gaussian p…
Tuning Fairness by Balancing Target Labels
Thomas Kehrenberg, Zexun Chen, Novi Quadrianto
The issue of fairness in machine learning models has recently attracted a lot of attention as ensuring it will ensure continued confidence of the general public in the deployment o…
Multivariate Gaussian and Student Process Regression for Multi-output Prediction
Zexun Chen, Bo Wang, Alexander N. Gorban
Gaussian process model for vector-valued function has been shown to be useful for multi-output prediction. The existing method for this model is to re-formulate the matrix-variate…
How priors of initial hyperparameters affect Gaussian process regression models
Zexun Chen, Bo Wang
The hyperparameters in Gaussian process regression (GPR) model with a specified kernel are often estimated from the data via the maximum marginal likelihood. Due to the non-convexi…