activity
20192025
most citedUtilizing machine learning to prevent water main breaks by understanding pipeline failure drivers

7 citations · 10 across the 10 of their papers we have counts for

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cs.LG2025

Multimodal Machine Learning for Real Estate Appraisal: A Comprehensive Survey

Chenya Huang, Zhidong Li, Fang Chen +1

Real estate appraisal has undergone a significant transition from manual to automated valuation and is entering a new phase of evolution. Leveraging comprehensive attention to vari…

cs.LG2024

Navigating Towards Fairness with Data Selection

Yixuan Zhang, Zhidong Li, Yang Wang +3

Machine learning algorithms often struggle to eliminate inherent data biases, particularly those arising from unreliable labels, which poses a significant challenge in ensuring fai…

cs.LG2024

TransFeat-TPP: An Interpretable Deep Covariate Temporal Point Processes

Zizhuo Meng, Boyu Li, Xuhui Fan +4

The classical temporal point process (TPP) constructs an intensity function by taking the occurrence times into account. Nevertheless, occurrence time may not be the only relevant…

cs.LG2022

De-biased Representation Learning for Fairness with Unreliable Labels

Yixuan Zhang, Feng Zhou, Zhidong Li +2

Removing bias while keeping all task-relevant information is challenging for fair representation learning methods since they would yield random or degenerate representations w.r.t.…

cs.LG2021

Bias-Tolerant Fair Classification

Yixuan Zhang, Feng Zhou, Zhidong Li +2

The label bias and selection bias are acknowledged as two reasons in data that will hinder the fairness of machine-learning outcomes. The label bias occurs when the labeling decisi…

cs.LG2020★ 1 cited

Long-Term Pipeline Failure Prediction Using Nonparametric Survival Analysis

Dilusha Weeraddana, Sudaraka MallawaArachchi, Tharindu Warnakula +2

Australian water infrastructure is more than a hundred years old, thus has begun to show its age through water main failures. Our work concerns approximately half a million pipelin…

cs.LG2019★ 1 cited

Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation

Feng Zhou, Zhidong Li, Xuhui Fan +3

In this paper, we consider the sigmoid Gaussian Hawkes process model: the baseline intensity and triggering kernel of Hawkes process are both modeled as the sigmoid transformation…