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Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel

The Journal of artificial intelligence research, 2021, Vol.71, p.667-695

2021

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Isolation Forest

2008 Eighth IEEE International Conference on Data Mining, 2008, p.413-422

2008

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Classifying under computational resource constraints : anytime classification using probabilistic estimators

Machine learning, 2007-10, Vol.69 (1), p.35-53

2007

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New Class Adaptation Via Instance Generation in One-Pass Class Incremental Learning

2017 IEEE International Conference on Data Mining (ICDM), 2017, p.1207-1212

2017

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The impact of isolation kernel on agglomerative hierarchical clustering algorithms

Pattern recognition, 2023-07, Vol.139, p.109517, Article 109517

2023

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Spectral-Spatial Anomaly Detection of Hyperspectral Data Based on Improved Isolation Forest

IEEE transactions on geoscience and remote sensing, 2022, Vol.60, p.1-16

2022

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CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities

Pattern recognition, 2021-09, Vol.117, p.107977, Article 107977

2021

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A new distributional treatment for time series and an anomaly detection investigation

Proceedings of the VLDB Endowment, 2022-07, Vol.15 (11), p.2321-2333

2022

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To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators

IEEE transactions on knowledge and data engineering, 2007-12, Vol.19 (12), p.1652-1665

2007

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A Principled Distributional Approach to Trajectory Similarity Measurement and its Application to Anomaly Detection

The Journal of artificial intelligence research, 2024-01, Vol.79, p.865-893

2024

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LOCAL MODELS-THE KEY TO BOOSTING STABLE LEARNERS SUCCESSFULLY

Computational intelligence, 2013-05, Vol.29 (2), p.331-356

2013

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Isolation Distributional Kernel: A New Tool for Kernel based Anomaly Detection

Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020, p.198-206

2020

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Hierarchical clustering that takes advantage of both density-peak and density-connectivity

Information systems (Oxford), 2022-01, Vol.103, p.101871, Article 101871

2022

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Improving Deep Forest by Screening

IEEE transactions on knowledge and data engineering, 2022-09, Vol.34 (9), p.4298-4312

2022

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Improving Deep Forest by Confidence Screening

2018 IEEE International Conference on Data Mining (ICDM), 2018, p.1194-1199

2018

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Multi-Label Learning with Emerging New Labels

IEEE transactions on knowledge and data engineering, 2018-10, Vol.30 (10), p.1901-1914

2018

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Grouping points by shared subspaces for effective subspace clustering

Pattern recognition, 2018-11, Vol.83, p.230-244

2018

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Is it possible to find the single nearest neighbor of a query in high dimensions?

Artificial intelligence, 2024-11, Vol.336, p.104206, Article 104206

2024

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Point-Set Kernel Clustering

IEEE transactions on knowledge and data engineering, 2023-05, Vol.35 (5), p.5147-5158

2023

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A new simple and efficient density estimator that enables fast systematic search

Pattern recognition letters, 2019-05, Vol.122, p.92-98

2019

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Ensemble selection for SuperParent-One-Dependence Estimators

Lecture notes in computer science, 2005, p.102-112

2005

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Maximizing Tree Diversity by Building Complete-Random Decision Trees

Advances in Knowledge Discovery and Data Mining, 2005, p.605-610

2005

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DEMass: a new density estimator for big data

Knowledge and information systems, 2013-06, Vol.35 (3), p.493-524

2013

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Isolation Distributional Kernel: A New Tool for Point and Group Anomaly Detections

IEEE transactions on knowledge and data engineering, 2023-03, Vol.35 (3), p.2697-2710

2023

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A new distributional treatment for time series anomaly detection

The VLDB journal, 2024-05, Vol.33 (3), p.753-780

2024

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Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel

Isolation Forest

Classifying under computational resource constraints : anytime classification using probabilistic estimators

New Class Adaptation Via Instance Generation in One-Pass Class Incremental Learning

The impact of isolation kernel on agglomerative hierarchical clustering algorithms

Spectral-Spatial Anomaly Detection of Hyperspectral Data Based on Improved Isolation Forest

CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities

A new distributional treatment for time series and an anomaly detection investigation

To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators

A Principled Distributional Approach to Trajectory Similarity Measurement and its Application to Anomaly Detection

LOCAL MODELS-THE KEY TO BOOSTING STABLE LEARNERS SUCCESSFULLY

Isolation Distributional Kernel: A New Tool for Kernel based Anomaly Detection

Hierarchical clustering that takes advantage of both density-peak and density-connectivity

Improving Deep Forest by Screening

Improving Deep Forest by Confidence Screening

Multi-Label Learning with Emerging New Labels

Grouping points by shared subspaces for effective subspace clustering

Is it possible to find the single nearest neighbor of a query in high dimensions?

Point-Set Kernel Clustering

A new simple and efficient density estimator that enables fast systematic search

Ensemble selection for SuperParent-One-Dependence Estimators

Maximizing Tree Diversity by Building Complete-Random Decision Trees

DEMass: a new density estimator for big data

Isolation Distributional Kernel: A New Tool for Point and Group Anomaly Detections

A new distributional treatment for time series anomaly detection

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