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Jonathan R. Wells

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Journal Articles

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2023
[j11]
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Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Hang Zhang, Ye Zhu:
Isolation Kernel Estimators. Knowl. Inf. Syst. 65(2): 759-787 (2023)
[j10]
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Kai Ming Ting, Jonathan R. Wells, Ye Zhu:
Point-Set Kernel Clustering. IEEE Trans. Knowl. Data Eng. 35(5): 5147-5158 (2023)
2021
[j9]
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  - journals/datamine/TingWW21
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Kai Ming Ting, Jonathan R. Wells, Takashi Washio:
Isolation kernel: the X factor in efficient and effective large scale online kernel learning. Data Min. Knowl. Discov. 35(6): 2282-2312 (2021)
2020
[j8]
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  - journals/kais/WellsAT20
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Jonathan R. Wells, Sunil Aryal, Kai Ming Ting:
Simple supervised dissimilarity measure: Bolstering iForest-induced similarity with class information without learning. Knowl. Inf. Syst. 62(8): 3203-3216 (2020)
2019
[j7]
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Jonathan R. Wells, Kai Ming Ting:
A new simple and efficient density estimator that enables fast systematic search. Pattern Recognit. Lett. 122: 92-98 (2019)
2018
[j6]
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  - journals/ci/BandaragodaTALZ18
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Tharindu R. Bandaragoda, Kai Ming Ting, David W. Albrecht, Fei Tony Liu, Ye Zhu, Jonathan R. Wells:
Isolation-based anomaly detection using nearest-neighbor ensembles. Comput. Intell. 34(4): 968-998 (2018)
2017
[j5]
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Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Sunil Aryal:
Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors. Mach. Learn. 106(1): 55-91 (2017)
2014
[j4]
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Jonathan R. Wells, Kai Ming Ting, Takashi Washio:
LiNearN: A new approach to nearest neighbour density estimator. Pattern Recognit. 47(8): 2702-2720 (2014)
2013
[j3]
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Kai Ming Ting, Lian Zhu, Jonathan R. Wells:
Local Models - the Key to Boosting Stable Learners Successfully. Comput. Intell. 29(2): 331-356 (2013)
[j2]
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Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu, Sunil Aryal:
DEMass: a new density estimator for big data. Knowl. Inf. Syst. 35(3): 493-524 (2013)
2011
[j1]
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Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb:
Feature-subspace aggregating: ensembles for stable and unstable learners. Mach. Learn. 82(3): 375-397 (2011)

Conference and Workshop Papers

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2021
[c8]
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Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Hang Zhang:
Isolation Kernel Density Estimation. ICDM 2021: 619-628
[c7]
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Sunil Aryal, Jonathan R. Wells:
Ensemble of Local Decision Trees for Anomaly Detection in Mixed Data. ECML/PKDD (1) 2021: 687-702
2014
[c6]
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Tharindu R. Bandaragoda, Kai Ming Ting, David W. Albrecht, Fei Tony Liu, Jonathan R. Wells:
Efficient Anomaly Detection by Isolation Using Nearest Neighbour Ensemble. ICDM Workshops 2014: 698-705
[c5]
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Sunil Aryal, Kai Ming Ting, Jonathan R. Wells, Takashi Washio:
Improving iForest with Relative Mass. PAKDD (2) 2014: 510-521
2012
[c4]
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  - conf/ausdm/WellsTC12
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Jonathan R. Wells, Kai Ming Ting, Naiwala P. Chandrasiri:
A non-time series approach to vehicle related time series problems. AusDM 2012: 61-70
2011
[c3]
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Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu:
Density Estimation Based on Mass. ICDM 2011: 715-724
2010
[c2]
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Kai Ming Ting, Jonathan R. Wells:
Multi-dimensional Mass Estimation and Mass-based Clustering. ICDM 2010: 511-520
2009
[c1]
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Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb:
FaSS: Ensembles for Stable Learners. MCS 2009: 364-374

Informal and Other Publications

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2024
[i4]
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  - journals/corr/abs-2401-11402
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Sunil Aryal, Jonathan R. Wells, Arbind Agrahari Baniya, KC Santosh:
Enabling clustering algorithms to detect clusters of varying densities through scale-invariant data preprocessing. CoRR abs/2401.11402 (2024)
2020
[i3]
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  - journals/corr/abs-2002-05815
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Kai Ming Ting, Jonathan R. Wells, Ye Zhu:
Clustering based on Point-Set Kernel. CoRR abs/2002.05815 (2020)
2019
[i2]
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  - journals/corr/abs-1907-01104
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Kai Ming Ting, Jonathan R. Wells, Takashi Washio:
Isolation Kernel: The X Factor in Efficient and Effective Large Scale Online Kernel Learning. CoRR abs/1907.01104 (2019)
2017
[i1]
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Jonathan R. Wells, Kai Ming Ting:
A simple efficient density estimator that enables fast systematic search. CoRR abs/1707.00783 (2017)

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