7 citations · 11 across the 7 of their papers we have counts for
7 papers
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.…
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…
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…
Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment Analysis
Sunny Verma, Jiwei Wang, Zhefeng Ge +5
Multimodal sentiment analysis utilizes multiple heterogeneous modalities for sentiment classification. The recent multimodal fusion schemes customize LSTMs to discover intra-modal…
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…
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…