8 papers
Matrix Profile for Anomaly Detection on Multidimensional Time Series
Chin-Chia Michael Yeh, Audrey Der, Uday Singh Saini +11
The Matrix Profile (MP), a versatile tool for time series data mining, has been shown effective in time series anomaly detection (TSAD). This paper delves into the problem of anoma…
A Systematic Evaluation of Generated Time Series and Their Effects in Self-Supervised Pretraining
Audrey Der, Chin-Chia Michael Yeh, Xin Dai +9
Self-supervised Pretrained Models (PTMs) have demonstrated remarkable performance in computer vision and natural language processing tasks. These successes have prompted researcher…
PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies
Audrey Der, Chin-Chia Michael Yeh, Yan Zheng +5
In recent years there has been significant progress in time series anomaly detection. However, after detecting an (perhaps tentative) anomaly, can we explain it? Such explanations…
Time Series Synthesis Using the Matrix Profile for Anonymization
Audrey Der, Chin-Chia Michael Yeh, Yan Zheng +6
Publishing and sharing data is crucial for the data mining community, allowing collaboration and driving open innovation. However, many researchers cannot release their data due to…
Temporal Treasure Hunt: Content-based Time Series Retrieval System for Discovering Insights
Chin-Chia Michael Yeh, Huiyuan Chen, Xin Dai +8
Time series data is ubiquitous across various domains such as finance, healthcare, and manufacturing, but their properties can vary significantly depending on the domain they origi…
Multitask Learning for Time Series Data with 2D Convolution
Chin-Chia Michael Yeh, Xin Dai, Yan Zheng +7
Multitask learning (MTL) aims to develop a unified model that can handle a set of closely related tasks simultaneously. By optimizing the model across multiple tasks, MTL generally…
An Efficient Content-based Time Series Retrieval System
Chin-Chia Michael Yeh, Huiyuan Chen, Xin Dai +9
A Content-based Time Series Retrieval (CTSR) system is an information retrieval system for users to interact with time series emerged from multiple domains, such as finance, health…
Toward a Foundation Model for Time Series Data
Chin-Chia Michael Yeh, Xin Dai, Huiyuan Chen +8
A foundation model is a machine learning model trained on a large and diverse set of data, typically using self-supervised learning-based pre-training techniques, that can be adapt…