20 citations · 25 across the 10 of their papers we have counts for
10 papers
Nearly Optimal Bayesian Inference for Structural Missingness
Chen Liang, Donghua Yang, Yutong Zhao +9
Structural missingness breaks 'just impute and train': values can be undefined by causal or logical constraints, and the mask may depend on observed variables, unobserved variables…
Exploring the Heterogeneity of Tabular Data: A Diversity-aware Data Generator via LLMs
Yafeng Tang, Xiaoou Ding, Jianzhuo Du +5
Tabular data generation has become increasingly essential for enabling robust machine learning applications, which require large-scale, high-quality data. Existing solutions levera…
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly Detection
Zhiyu Liang, Dongrui Cai, Chenyuan Zhang +6
Model selection has been raised as an essential problem in the area of time series anomaly detection (TSAD), because there is no single best TSAD model for the highly heterogeneous…
Revisiting Data Analysis with Pre-trained Foundation Models
Chen Liang, Donghua Yang, Zheng Liang +6
Data analysis focuses on harnessing advanced statistics, programming, and machine learning techniques to extract valuable insights from vast datasets. An increasing volume and vari…
TimeCSL: Unsupervised Contrastive Learning of General Shapelets for Explorable Time Series Analysis
Zhiyu Liang, Chen Liang, Zheng Liang +2
Unsupervised (a.k.a. Self-supervised) representation learning (URL) has emerged as a new paradigm for time series analysis, because it has the ability to learn generalizable time s…
Unsupervised Multi-modal Feature Alignment for Time Series Representation Learning
Chen Liang, Donghua Yang, Zhiyu Liang +4
In recent times, the field of unsupervised representation learning (URL) for time series data has garnered significant interest due to its remarkable adaptability across diverse do…
A Shapelet-based Framework for Unsupervised Multivariate Time Series Representation Learning
Zhiyu Liang, Jianfeng Zhang, Chen Liang +3
Recent studies have shown great promise in unsupervised representation learning (URL) for multivariate time series, because URL has the capability in learning generalizable represe…
UniTS: A Universal Time Series Analysis Framework Powered by Self-Supervised Representation Learning
Zhiyu Liang, Chen Liang, Zheng Liang +2
Machine learning has emerged as a powerful tool for time series analysis. Existing methods are usually customized for different analysis tasks and face challenges in tackling pract…
Exploring Data and Knowledge combined Anomaly Explanation of Multivariate Industrial Data
Xiaoou Ding, Hongzhi Wang, Chen Wang +2
The demand for high-performance anomaly detection techniques of IoT data becomes urgent, especially in industry field. The anomaly identification and explanation in time series dat…
Auto-CASH: Autonomous Classification Algorithm Selection with Deep Q-Network
Tianyu Mu, Hongzhi Wang, Chunnan Wang +1
The great amount of datasets generated by various data sources have posed the challenge to machine learning algorithm selection and hyperparameter configuration. For a specific mac…