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Kernel-based support vector machines for automated health status assessment in monitoring sensor data

International journal of advanced manufacturing technology, 2018-03, Vol.95 (1-4), p.327-340

2018

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A spectral-based clustering for structural health monitoring of the Sydney Harbour Bridge

Mechanical systems and signal processing, 2017-03, Vol.87, p.384-400

2017

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A scalable approach to spectral clustering with SDD solvers

Journal of intelligent information systems, 2015-04, Vol.44 (2), p.289-308

2015

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A Tensor-Based Structural Damage Identification and Severity Assessment

Sensors (Basel, Switzerland), 2018-01, Vol.18 (1), p.111

2018

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A clustering approach for structural health monitoring on bridges

Journal of civil structural health monitoring, 2016-07, Vol.6 (3), p.429-445

2016

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A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge

Structural health monitoring, 2019-01, Vol.18 (1), p.35-48

2019

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Incremental commute time and its online applications

Pattern recognition, 2019-04, Vol.88, p.101-112

2019

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Deep Conversational Recommender Systems: Challenges and Opportunities

Computer (Long Beach, Calif.), 2022-04, Vol.55 (4), p.30-39

2022

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Let Trajectories Speak Out the Traffic Bottlenecks

ACM transactions on intelligent systems and technology, 2022-02, Vol.13 (1), p.1-21

2022

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CupMar: A deep learning model for personalized news recommendation based on contextual user-profile and multi-aspect article representation

World wide web (Bussum), 2023-03, Vol.26 (2), p.713-732

2023

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On Damage Identification in Civil Structures Using Tensor Analysis

Advances in Knowledge Discovery and Data Mining, p.459-471

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Smart pothole detection system using vehicle-mounted sensors and machine learning

Journal of civil structural health monitoring, 2019-02, Vol.9 (1), p.91-102

2019

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Dual-Stage Bayesian Sequence to Sequence Embeddings for Energy Demand Forecasting

Advances in Knowledge Discovery and Data Mining, p.277-289

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Adaptive One-Class Support Vector Machine for Damage Detection in Structural Health Monitoring

Advances in Knowledge Discovery and Data Mining, p.42-57

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Energy Consumption Forecasting Using a Stacked Nonparametric Bayesian Approach

Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, p.19-35

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Long-Term Water Pipe Condition Assessment: A Semiparametric Model Using Gaussian Process and Survival Analysis

Advances in Knowledge Discovery and Data Mining, 2020, p.487-499

2020

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Machine learning based novel ensemble learning framework for electricity operational forecasting

Electric power systems research, 2021-12, Vol.201, p.107477, Article 107477

2021

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Online Data Fusion Using Incremental Tensor Learning

Advances in Knowledge Discovery and Data Mining, p.357-369

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Comparing multi-step ahead building cooling load prediction using shallow machine learning and deep learning models

Sustainable Energy, Grids and Networks, 2021-12, Vol.28, p.100543, Article 100543

2021

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Comparison of unsupervised shallow and deep models for structural health monitoring

Proceedings of the Institution of Civil Engineers. Bridge engineering, 2021-10, Vol.177 (2), p.107-117

2021

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Robust Deep Learning Methods for Anomaly Detection

Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020, p.3507-3508

2020

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Concept Drift Adaption for Online Anomaly Detection in Structural Health Monitoring

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019, p.2813-2821

2019

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HeteGraph: graph learning in recommender systems via graph convolutional networks

Neural computing & applications, 2023-06, Vol.35 (18), p.13047-13063

2023

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Automated parameter tuning in one-class support vector machine: an application for damage detection

International journal of data science and analytics, 2018-12, Vol.6 (4), p.311-325

2018

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Adaptive Online One-Class Support Vector Machines with Applications in Structural Health Monitoring

ACM transactions on intelligent systems and technology, 2018-11, Vol.9 (6), p.1-20

2018

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Kernel-based support vector machines for automated health status assessment in monitoring sensor data

A spectral-based clustering for structural health monitoring of the Sydney Harbour Bridge

A scalable approach to spectral clustering with SDD solvers

A Tensor-Based Structural Damage Identification and Severity Assessment

A clustering approach for structural health monitoring on bridges

A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge

Incremental commute time and its online applications

Deep Conversational Recommender Systems: Challenges and Opportunities

Let Trajectories Speak Out the Traffic Bottlenecks

CupMar: A deep learning model for personalized news recommendation based on contextual user-profile and multi-aspect article representation

On Damage Identification in Civil Structures Using Tensor Analysis

Smart pothole detection system using vehicle-mounted sensors and machine learning

Dual-Stage Bayesian Sequence to Sequence Embeddings for Energy Demand Forecasting

Adaptive One-Class Support Vector Machine for Damage Detection in Structural Health Monitoring

Energy Consumption Forecasting Using a Stacked Nonparametric Bayesian Approach

Long-Term Water Pipe Condition Assessment: A Semiparametric Model Using Gaussian Process and Survival Analysis

Machine learning based novel ensemble learning framework for electricity operational forecasting

Online Data Fusion Using Incremental Tensor Learning

Comparing multi-step ahead building cooling load prediction using shallow machine learning and deep learning models

Comparison of unsupervised shallow and deep models for structural health monitoring

Robust Deep Learning Methods for Anomaly Detection

Concept Drift Adaption for Online Anomaly Detection in Structural Health Monitoring

HeteGraph: graph learning in recommender systems via graph convolutional networks

Automated parameter tuning in one-class support vector machine: an application for damage detection

Adaptive Online One-Class Support Vector Machines with Applications in Structural Health Monitoring

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