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01/01/2023
A principled distributional approach to trajectory similarity measurement
Existing measures and representations for trajectories have two longstan...
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12/30/2022
Detecting Change Intervals with Isolation Distributional Kernel
Detecting abrupt changes in data distribution is one of the most signifi...
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09/29/2021
Breaking the curse of dimensionality with Isolation Kernel
The curse of dimensionality has been studied in different aspects. Howev...
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10/12/2020
The Impact of Isolation Kernel on Agglomerative Hierarchical Clustering Algorithms
Agglomerative hierarchical clustering (AHC) is one of the popular cluste...
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09/24/2020
Isolation Distributional Kernel: A New Tool for Point Group Anomaly Detection
We introduce Isolation Distributional Kernel as a new way to measure the...
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05/06/2020
A Comprehensive Survey on Outlying Aspect Mining Methods
In recent years, researchers have become increasingly interested in outl...
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04/28/2020
A new effective and efficient measure for outlying aspect mining
Outlying Aspect Mining (OAM) aims to find the subspaces (a.k.a. aspects)...
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02/14/2020
Clustering based on Point-Set Kernel
Measuring similarity between two objects is the core operation in existi...
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07/02/2019
Isolation Kernel: The X Factor in Efficient and Effective Large Scale Online Kernel Learning
Large scale online kernel learning aims to build an efficient and scalab...
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06/30/2019
Nearest-Neighbour-Induced Isolation Similarity and its Impact on Density-Based Clustering
A recent proposal of data dependent similarity called Isolation Kernel/S...
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06/24/2019
Improving Stochastic Neighbour Embedding fundamentally with a well-defined data-dependent kernel
We identify a fundamental issue in the popular Stochastic Neighbour Embe...
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02/09/2019
A new simple and effective measure for bag-of-word inter-document similarity measurement
To measure the similarity of two documents in the bag-of-words (BoW) vec...
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10/08/2018
Hierarchical clustering that takes advantage of both density-peak and density-connectivity
This paper focuses on density-based clustering, particularly the Density...
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10/05/2018
CDF Transform-Shift: An effective way to deal with inhomogeneous density datasets
Many distance-based algorithms exhibit bias towards dense clusters in in...
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07/03/2017
