Search Results for author: Lijun Sun

Found 38 papers, 17 papers with code

Bayesian Temporal Factorization for Multidimensional Time Series Prediction

3 code implementations14 Oct 2019 Xinyu Chen, Lijun Sun

In this paper, we propose a Bayesian temporal factorization (BTF) framework for modeling multidimensional time series -- in particular spatiotemporal data -- in the presence of missing values.

Imputation Time Series +1

A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation

1 code implementation23 Mar 2020 Xinyu Chen, Jinming Yang, Lijun Sun

Sparsity and missing data problems are very common in spatiotemporal traffic data collected from various sensing systems.

Imputation Traffic Data Imputation

Scalable Low-Rank Tensor Learning for Spatiotemporal Traffic Data Imputation

2 code implementations7 Aug 2020 Xinyu Chen, Yixian Chen, Nicolas Saunier, Lijun Sun

Recent studies based on tensor nuclear norm have demonstrated the superiority of tensor learning in imputation tasks by effectively characterizing the complex correlations/dependencies in spatiotemporal data.

Imputation Traffic Data Imputation

Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation

1 code implementation30 Apr 2021 Xinyu Chen, MengYing Lei, Nicolas Saunier, Lijun Sun

In this paper, we propose a low-rank autoregressive tensor completion (LATC) framework by introducing \textit{temporal variation} as a new regularization term into the completion of a third-order (sensor $\times$ time of day $\times$ day) tensor.

Imputation Time Series +2

Laplacian Convolutional Representation for Traffic Time Series Imputation

1 code implementation3 Dec 2022 Xinyu Chen, Zhanhong Cheng, Nicolas Saunier, Lijun Sun

In this study, we first introduce a Laplacian kernel to temporal regularization for characterizing local trends in traffic time series, which can be formulated in the form of circular convolution.

Decision Making Image Inpainting +4

Low-Rank Autoregressive Tensor Completion for Multivariate Time Series Forecasting

1 code implementation18 Jun 2020 Xinyu Chen, Lijun Sun

In this paper, we propose a low-rank autoregressive tensor completion (LATC) framework to model multivariate time series data.

Imputation Multivariate Time Series Forecasting +2

Inductive Graph Neural Networks for Spatiotemporal Kriging

1 code implementation13 Jun 2020 Yuankai Wu, Dingyi Zhuang, Aurelie Labbe, Lijun Sun

Time series forecasting and spatiotemporal kriging are the two most important tasks in spatiotemporal data analysis.

Time Series Time Series Forecasting

Efficient Motion Planning for Automated Lane Change based on Imitation Learning and Mixed-Integer Optimization

1 code implementation18 Apr 2019 Chenyang Xi, Tianyu Shi, Yuankai Wu, Lijun Sun

Traditional motion planning methods suffer from several drawbacks in terms of optimality, efficiency and generalization capability.

Action Generation Autonomous Driving +2

Discovering Dynamic Patterns from Spatiotemporal Data with Time-Varying Low-Rank Autoregression

1 code implementation28 Nov 2022 Xinyu Chen, ChengYuan Zhang, Xiaoxu Chen, Nicolas Saunier, Lijun Sun

In the temporal context, the complex time-varying system behaviors can be revealed by the temporal modes in the proposed model.

Model Compression

Toward multi-target self-organizing pursuit in a partially observable Markov game

1 code implementation24 Jun 2022 Lijun Sun, Yu-Cheng Chang, Chao Lyu, Ye Shi, Yuhui Shi, Chin-Teng Lin

The proposed distributed algorithm: fuzzy self-organizing cooperative coevolution (FSC2) is then leveraged to resolve the three challenges in multi-target SOP: distributed self-organizing search (SOS), distributed task allocation, and distributed single-target pursuit.

Decision Making Multi-Agent Path Finding +1

Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach

1 code implementation2 Aug 2023 Chunwei Yang, Xiaoxu Chen, Lijun Sun, Hongyu Yang, Yuankai Wu

To address this gap, we propose an unsupervised method called Floss that automatically regularizes learned representations in the frequency domain.

Anomaly Detection Representation Learning +3

Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging

1 code implementation24 Sep 2021 Yuankai Wu, Dingyi Zhuang, MengYing Lei, Aurelie Labbe, Lijun Sun

Specifically, we propose a novel spatial aggregation network (SAN) inspired by Principal Neighborhood Aggregation, which uses multiple aggregation functions to help one node gather diverse information from its neighbors.

Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach

1 code implementation4 Dec 2023 Jinguo Cheng, Ke Li, Yuxuan Liang, Lijun Sun, Junchi Yan, Yuankai Wu

To address this challenge, we present the Super-Multivariate Urban Mobility Transformer (SUMformer), which utilizes a specially designed attention mechanism to calculate temporal and cross-variable correlations and reduce computational costs stemming from a large number of time series.

Multivariate Time Series Forecasting Time Series +1

Cooperative coevolution of real predator robots and virtual robots in the pursuit domain

1 code implementation23 Jan 2019 Lijun Sun, Chao Lyu, Yuhui Shi

This paper presents a particle swarm optimization (PSO) based cooperative coevolutionary algorithm for the (predator) robots, called CCPSO-R, where real and virtual robots coexist in an evolutionary algorithm (EA).

Robotics Multiagent Systems

Low-Rank Hankel Tensor Completion for Traffic Speed Estimation

1 code implementation21 May 2021 Xudong Wang, Yuankai Wu, Dingyi Zhuang, Lijun Sun

This paper studies the traffic state estimation (TSE) problem using sparse observations from mobile sensors.

Matrix Completion

Incremental Bayesian tensor learning for structural monitoring data imputation and response forecasting

no code implementations1 Jul 2020 Pu Ren, Xinyu Chen, Lijun Sun, Hao Sun

To address this fundamental issue, this paper presents an incremental Bayesian tensor learning method for reconstruction of spatiotemporal missing data in SHM and forecasting of structural response.

Imputation Incremental Learning +1

Efficient Connected and Automated Driving System with Multi-agent Graph Reinforcement Learning

no code implementations6 Jul 2020 Tianyu Shi, Jiawei Wang, Yuankai Wu, Luis Miranda-Moreno, Lijun Sun

Instead of learning a reliable behavior for ego automated vehicle, we focus on how to improve the outcomes of the total transportation system by allowing each automated vehicle to learn cooperation with each other and regulate human-driven traffic flow.

Decision Making reinforcement-learning +1

Industrial Topics in Urban Labor System

no code implementations18 Sep 2020 Jaehyuk Park, Morgan R. Frank, Lijun Sun, Hyejin Youn

It is therefore important to recognize that classification system are not necessarily static, especially for economic systems, and even more so in urban areas where most innovation takes place and is implemented.

Classification General Classification

One Vertex Attack on Graph Neural Networks-based Spatiotemporal Forecasting

no code implementations1 Jan 2021 Fuqiang Liu, Luis Miranda Moreno, Lijun Sun

Empirical studies prove that perturbations in one vertex can be diffused into most of the graph when spatiotemporal GNNs are under One Vertex Attack.

Graph Classification

Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning

no code implementations2 May 2021 Jiawei Wang, Lijun Sun

However, due to the significant uncertainties in passenger demand and traffic conditions, bus operation is unstable in nature and bus bunching has become a common phenomenon that undermines the reliability and efficiency of bus services.

Graph Attention Multi-agent Reinforcement Learning +2

Scalable Spatiotemporally Varying Coefficient Modelling with Bayesian Kernelized Tensor Regression

no code implementations31 Aug 2021 MengYing Lei, Aurelie Labbe, Lijun Sun

To address this challenge, we summarize the spatiotemporally varying coefficients using a third-order tensor structure and propose to reformulate the spatiotemporally varying coefficient model as a special low-rank tensor regression problem.

regression

Individual Mobility Prediction via Attentive Marked Temporal Point Processes

no code implementations6 Sep 2021 Yuankai Wu, Zhanhong Cheng, Lijun Sun

Individual mobility prediction is an essential task for transportation demand management and traffic system operation.

Management Point Processes

Spatially Focused Attack against Spatiotemporal Graph Neural Networks

no code implementations10 Sep 2021 Fuqiang Liu, Luis Miranda-Moreno, Lijun Sun

However, despite that recent studies have demonstrated that deep neural networks (DNNs) are vulnerable to carefully designed perturbations in multiple domains like objection classification and graph representation, current adversarial works cannot be directly applied to spatiotemporal forecasting due to the causal nature and spatiotemporal mechanisms in forecasting models.

Management Traffic Prediction

Dynamic Spatiotemporal Graph Convolutional Neural Networks for Traffic Data Imputation with Complex Missing Patterns

no code implementations17 Sep 2021 Yuebing Liang, Zhan Zhao, Lijun Sun

The results show that our proposed model outperforms existing deep learning models in all kinds of missing scenarios and the graph structure estimation technique contributes to the model performance.

Imputation Traffic Data Imputation

Hankel-structured Tensor Robust PCA for Multivariate Traffic Time Series Anomaly Detection

no code implementations8 Oct 2021 Xudong Wang, Luis Miranda-Moreno, Lijun Sun

We treat the raw data with anomalies as a multivariate time series matrix (location $\times$ time) and assume the denoised matrix has a low-rank structure.

Anomaly Detection Time Series +1

Robust Dynamic Bus Control: A Distributional Multi-agent Reinforcement Learning Approach

no code implementations2 Nov 2021 Jiawei Wang, Lijun Sun

However, the operation of a bus fleet is unstable in nature, and bus bunching has become a common phenomenon that undermines the efficiency and reliability of bus systems.

Continuous Control Meta-Learning +3

Bayesian Complementary Kernelized Learning for Multidimensional Spatiotemporal Data

no code implementations21 Aug 2022 MengYing Lei, Aurelie Labbe, Lijun Sun

Probabilistic modeling of multidimensional spatiotemporal data is critical to many real-world applications.

Gaussian Processes

Scalable Dynamic Mixture Model with Full Covariance for Probabilistic Traffic Forecasting

no code implementations10 Dec 2022 Seongjin Choi, Nicolas Saunier, Vincent Zhihao Zheng, Martin Trepanier, Lijun Sun

Deep learning-based multivariate and multistep-ahead traffic forecasting models are typically trained with the mean squared error (MSE) or mean absolute error (MAE) as the loss function in a sequence-to-sequence setting, simply assuming that the errors follow an independent and isotropic Gaussian or Laplacian distributions.

Enhancing Deep Traffic Forecasting Models with Dynamic Regression

no code implementations17 Jan 2023 Vincent Zhihao Zheng, Seongjin Choi, Lijun Sun

A common assumption in deep learning-based multivariate and multistep traffic time series forecasting models is that residuals are independent, isotropic, and uncorrelated in space and time.

regression Time Series +1

Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimization

no code implementations28 Feb 2023 MengYing Lei, Lijun Sun

However, such simple kernel specifications are deficient in learning functions with complex features, such as being nonstationary, nonseparable, and multimodal.

Bayesian Optimization Gaussian Processes +1

Better Batch for Deep Probabilistic Time Series Forecasting

no code implementations26 May 2023 Vincent Zhihao Zheng, Seongjin Choi, Lijun Sun

Our method constructs a mini-batch as a collection of $D$ consecutive time series segments for model training.

Decision Making Probabilistic Time Series Forecasting +2

Tensor Dirichlet Process Multinomial Mixture Model for Passenger Trajectory Clustering

no code implementations23 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.

Clustering Trajectory Clustering

Choose A Table: Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering

no code implementations31 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.

Clustering Community Detection +1

A Critical Perceptual Pre-trained Model for Complex Trajectory Recovery

no code implementations5 Nov 2023 Dedong Li, Ziyue Li, Zhishuai Li, Lei Bai, Qingyuan Gong, Lijun Sun, Wolfgang Ketter, Rui Zhao

Then, we propose a Multi-view Graph and Complexity Aware Transformer (MGCAT) model to encode these semantics in trajectory pre-training from two aspects: 1) adaptively aggregate the multi-view graph features considering trajectory pattern, and 2) higher attention to critical nodes in a complex trajectory.

Multivariate Probabilistic Time Series Forecasting with Correlated Errors

no code implementations1 Feb 2024 Vincent Zhihao Zheng, Lijun Sun

Modeling the correlations among errors is closely associated with how accurately the model can quantify predictive uncertainty in probabilistic time series forecasting.

Probabilistic Time Series Forecasting Time Series +1

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