Jonathan R. Wells

25 papers A* 3A 1Misc 1Journal 16Unranked 4
YearRankTypeTitle / Venue / Authors
2025 A conf
HI-PMK: A Data-Dependent Kernel for Incomplete Heterogeneous Data Representation.
ECAI
Youran Zhou, Mohamed Reda Bouadjenek, Jonathan R. Wells, Sunil Aryal
2025 J jnl
Handling Incomplete Heterogeneous Data using a Data-Dependent Kernel.
CoRR
Youran Zhou, Mohamed Reda Bouadjenek, Jonathan R. Wells, Sunil Aryal
2024 J jnl
Enabling clustering algorithms to detect clusters of varying densities through scale-invariant data preprocessing.
CoRR
Sunil Aryal, Jonathan R. Wells, Arbind Agrahari Baniya, KC Santosh
2023 J jnl
Isolation Kernel Estimators.
Knowl. Inf. Syst.
Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Hang Zhang, Ye Zhu
2023 J jnl
Point-Set Kernel Clustering.
IEEE Trans. Knowl. Data Eng.
Kai Ming Ting, Jonathan R. Wells, Ye Zhu
2021 — conf
Ensemble of Local Decision Trees for Anomaly Detection in Mixed Data.
ECML/PKDD (1)
Sunil Aryal, Jonathan R. Wells
2021 A* conf
Isolation Kernel Density Estimation.
ICDM
Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Hang Zhang
2021 J jnl
Isolation kernel: the X factor in efficient and effective large scale online kernel learning.
Data Min. Knowl. Discov.
Kai Ming Ting, Jonathan R. Wells, Takashi Washio
2020 J jnl
Clustering based on Point-Set Kernel.
CoRR
Kai Ming Ting, Jonathan R. Wells, Ye Zhu
2020 J jnl
Simple supervised dissimilarity measure: Bolstering iForest-induced similarity with class information without learning.
Knowl. Inf. Syst.
Jonathan R. Wells, Sunil Aryal, Kai Ming Ting
2019 J jnl
A new simple and efficient density estimator that enables fast systematic search.
Pattern Recognit. Lett.
Jonathan R. Wells, Kai Ming Ting
2019 J jnl
Isolation Kernel: The X Factor in Efficient and Effective Large Scale Online Kernel Learning.
CoRR
Kai Ming Ting, Jonathan R. Wells, Takashi Washio
2018 J jnl
Isolation-based anomaly detection using nearest-neighbor ensembles.
Comput. Intell.
Tharindu R. Bandaragoda, Kai Ming Ting, David W. Albrecht, Fei Tony Liu, Ye Zhu, Jonathan R. Wells
2017 J jnl
A simple efficient density estimator that enables fast systematic search.
CoRR
Jonathan R. Wells, Kai Ming Ting
2017 J jnl
Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors.
Mach. Learn.
Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Sunil Aryal
2014 — conf
Efficient Anomaly Detection by Isolation Using Nearest Neighbour Ensemble.
ICDM Workshops
Tharindu R. Bandaragoda, Kai Ming Ting, David W. Albrecht, Fei Tony Liu, Jonathan R. Wells
2014 — conf
Improving iForest with Relative Mass.
PAKDD (2)
Sunil Aryal, Kai Ming Ting, Jonathan R. Wells, Takashi Washio
2014 J jnl
LiNearN: A new approach to nearest neighbour density estimator.
Pattern Recognit.
Jonathan R. Wells, Kai Ming Ting, Takashi Washio
2013 J jnl
DEMass: a new density estimator for big data.
Knowl. Inf. Syst.
Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu, Sunil Aryal
2013 J jnl
Local Models - the Key to Boosting Stable Learners Successfully.
Comput. Intell.
Kai Ming Ting, Lian Zhu, Jonathan R. Wells
2012 Misc conf
A non-time series approach to vehicle related time series problems.
AusDM
Jonathan R. Wells, Kai Ming Ting, Naiwala P. Chandrasiri
2011 A* conf
Density Estimation Based on Mass.
ICDM
Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu
2011 J jnl
Feature-subspace aggregating: ensembles for stable and unstable learners.
Mach. Learn.
Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb
2010 A* conf
Multi-dimensional Mass Estimation and Mass-based Clustering.
ICDM
Kai Ming Ting, Jonathan R. Wells
2009 — conf
FaSS: Ensembles for Stable Learners.
MCS
Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb