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researcher

Fang Chen

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CY1
  • stat.AP1
same name
  • Fang Chen — 15 papers
  • Fang Chen — 6 papers, h 16
  • Fang Chen — 4 papers
  • Fang Chen — 3 papers
  • Fang Chen — 3 papers
  • Fang Chen — 3 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192021
most citedUtilizing machine learning to prevent water main breaks by understanding pipeline failure drivers

7 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

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.CY2020★ 7 cited

Utilizing machine learning to prevent water main breaks by understanding pipeline failure drivers

Dilusha Weeraddana, Bin Liang, Zhidong Li +5

Data61 and Western Water worked collaboratively to apply engineering expertise and Machine Learning tools to find a cost-effective solution to the pipe failure problem in the regio…

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…

stat.AP2019

Fast Multi-resolution Segmentation for Nonstationary Hawkes Process Using Cumulants

Feng Zhou, Zhidong Li, Xuhui Fan +3

The stationarity is assumed in vanilla Hawkes process, which reduces the model complexity but introduces a strong assumption. In this paper, we propose a fast multi-resolution segm…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.