78 citations · 91 across the 14 of their papers we have counts for
14 papers
Statistical Depth for Interval Data: A Closeness-Based Approach and Its Applications
Xiaozheng Chen, Wenlin Dai
With the rapid development of technology, interval data have been increasingly widely used in various fields, as they can effectively carry information on measurement uncertainty a…
Fast robust location and scatter estimation: a depth-based method
Maoyu Zhang, Yan Song, Wenlin Dai
The minimum covariance determinant (MCD) estimator is ubiquitous in multivariate analysis, the critical step of which is to select a subset of a given size with the lowest sample c…
Learning Brain Connectivity in Social Cognition with Dynamic Network Regression
Maoyu Zhang, Biao Cai, Wenlin Dai +3
Dynamic networks have been increasingly used to characterize brain connectivity that varies during resting and task states. In such characterizations, a connectivity network is typ…
Global Depths for Irregularly Observed Multivariate Functional Data
Zhuo Qu, Wenlin Dai, Marc G. Genton
Two frameworks for multivariate functional depth based on multivariate depths are introduced in this paper. The first framework is multivariate functional integrated depth, and the…
Lexicon-injected Semantic Parsing for Task-Oriented Dialog
Xiaojun Meng, Wenlin Dai, Yasheng Wang +4
Recently, semantic parsing using hierarchical representations for dialog systems has captured substantial attention. Task-Oriented Parse (TOP), a tree representation with intents a…
Fast Community Detection in Dynamic and Heterogeneous Networks
Maoyu Zhang, Jingfei Zhang, Wenlin Dai
Dynamic heterogeneous networks describe the temporal evolution of interactions among nodes and edges of different types. While there is a rich literature on finding communities in…
Large-Scale Low-Rank Gaussian Process Prediction with Support Points
Yan Song, Wenlin Dai, Marc G. Genton
Low-rank approximation is a popular strategy to tackle the "big n problem" associated with large-scale Gaussian process regressions. Basis functions for developing low-rank structu…
Robust Two-Layer Partition Clustering of Sparse Multivariate Functional Data
Zhuo Qu, Wenlin Dai, Marc G. Genton
A novel elastic time distance for sparse multivariate functional data is proposed and used to develop a robust distance-based two-layer partition clustering method. With this propo…
An End-to-end Chinese Text Normalization Model based on Rule-guided Flat-Lattice Transformer
Wenlin Dai, Changhe Song, Xiang Li +4
Text normalization, defined as a procedure transforming non standard words to spoken-form words, is crucial to the intelligibility of synthesized speech in text-to-speech system. R…
Trajectory Functional Boxplots
Zonghui Yao, Wenlin Dai, Marc G. Genton
With the development of data-monitoring techniques in various fields of science, multivariate functional data are often observed. Consequently, an increasing number of methods have…
Functional Outlier Detection and Taxonomy by Sequential Transformations
Wenlin Dai, Tomas Mrkvicka, Ying Sun +1
Functional data analysis can be seriously impaired by abnormal observations, which can be classified as either magnitude or shape outliers based on their way of deviating from the…
An Outlyingness Matrix for Multivariate Functional Data Classification
Wenlin Dai, Marc G. Genton
The classification of multivariate functional data is an important task in scientific research. Unlike point-wise data, functional data are usually classified by their shapes rathe…
Multivariate Functional Data Visualization and Outlier Detection
Wenlin Dai, Marc G. Genton
This article proposes a new graphical tool, the magnitude-shape (MS) plot, for visualizing both the magnitude and shape outlyingness of multivariate functional data. The proposed t…
Directional Outlyingness for Multivariate Functional Data
Wenlin Dai, Marc G. Genton
The direction of outlyingness is crucial to describing the centrality of multivariate functional data. Motivated by this idea, we generalize classical depth to directional outlying…