1 code implementation • 3 May 2024 • Jiexia Ye, Weiqi Zhang, Ke Yi, Yongzi Yu, Ziyue Li, Jia Li, Fugee Tsung
There are two main research lines, namely pre-training foundation models from scratch for time series and adapting large language foundation models for time series.
no code implementations • 5 Apr 2024 • Jiuyun Hu, Ziyue Li, Chen Zhang, Fugee Tsung, Hao Yan
Moreover, a case study in the station clustering based on real passenger flow data is conducted, with quite valuable insights discovered.
no code implementations • 31 Jan 2024 • YanRong Li, Juan Du, Fugee Tsung, Wei Jiang
This paper proposes a novel process control and monitoring method for the complex structure of high-dimensional image-based overlay errors (modeled in tensor form), which are collected in semiconductor manufacturing processes.
1 code implementation • 14 Dec 2023 • Jiaqi Tang, Hao Lu, Xiaogang Xu, Ruizheng Wu, Sixing Hu, Tong Zhang, Tsz Wa Cheng, Ming Ge, Ying-Cong Chen, Fugee Tsung
Artificial Intelligence (AI)-driven defect inspection is pivotal in industrial manufacturing.
no code implementations • 31 Oct 2023 • Ziyue Li, Hao Yan, Chen Zhang, Lijun Sun, Wolfgang Ketter, Fugee Tsung
In this paper, we propose a novel tensor Dirichlet Process Multinomial Mixture model with graphs, which can preserve the hierarchical structure of the multi-dimensional trip information and cluster them in a unified one-step manner with the ability to determine the number of clusters automatically.
no code implementations • 25 Aug 2023 • Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong
Furthermore, we offer theoretical insights into SEGNO, highlighting that it can learn a unique trajectory between adjacent states, which is crucial for model generalization.
no code implementations • 24 Aug 2023 • Weiqi Zhang, Jianfeng Zhang, Jia Li, Fugee Tsung
Based on this, we create two views for the input time series through two different encoders.
no code implementations • 23 Jun 2023 • Ziyue Li, Hao Yan, Chen Zhang, Andi Wang, Wolfgang Ketter, Lijun Sun, Fugee Tsung
In this paper, we propose a novel Tensor Dirichlet Process Multinomial Mixture model (Tensor-DPMM), which is designed to preserve the multi-mode and hierarchical structure of the multi-dimensional trip information via tensor, and cluster them in a unified one-step manner.
1 code implementation • 12 Jun 2023 • Luxuan Wang, Lei Bai, Ziyue Li, Rui Zhao, Fugee Tsung
We evaluated the effectiveness and flexibility of our representation learning framework on correlated time series forecasting and cold-start transferring the forecasting model to new instances with limited data.
Correlated Time Series Forecasting Representation Learning +1
1 code implementation • 5 Jun 2023 • Tian Lan, Ziyue Li, Zhishuai Li, Lei Bai, Man Li, Fugee Tsung, Wolfgang Ketter, Rui Zhao, Chen Zhang
This encourages the multi-task design: with each DAG as a task, the MM-DAG tries to learn the multiple DAGs jointly so that their consensus and consistency are maximized.
1 code implementation • 10 Apr 2023 • Weiqi Zhang, Guanlve Li, Jianheng Tang, Jia Li, Fugee Tsung
Data imputation is a prevalent and important task due to the ubiquitousness of missing data.
1 code implementation • 30 Jan 2023 • Jianheng Tang, Weiqi Zhang, Jiajin Li, Kangfei Zhao, Fugee Tsung, Jia Li
As the graphs to be aligned are usually constructed from different sources, the inconsistency issues of structures and features between two graphs are ubiquitous in real-world applications.
no code implementations • 12 Dec 2022 • Yang Liu, Yu Rong, Zhuoning Guo, Nuo Chen, Tingyang Xu, Fugee Tsung, Jia Li
To address these challenges, we formulate the micro perspective mobility modeling into computing the relevance score between a diffusion and a location, conditional on a geometric graph.
no code implementations • 30 Nov 2022 • Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Tingyang Xu, Peilin Zhao, Lanqing Li, Fugee Tsung, Jia Li
In this work, we present a regularized graph autoencoder for graph attribute imputation, named MEGAE, which aims at mitigating spectral concentration problem by maximizing the graph spectral entropy.
1 code implementation • 26 Jun 2022 • Jiashun Cheng, Man Li, Jia Li, Fugee Tsung
Graph self-supervised learning (SSL) has been vastly employed to learn representations from unlabeled graphs.
no code implementations • 23 Apr 2020 • Ziyue Li, Hao Yan, Chen Zhang, Fugee Tsung
Spatiotemporal data is very common in many applications, such as manufacturing systems and transportation systems.
1 code implementation • 11 Dec 2019 • Ziyue Li, Nurettin Dorukhan Sergin, Hao Yan, Chen Zhang, Fugee Tsung
Low-rank tensor decomposition and completion have attracted significant interest from academia given the ubiquity of tensor data.