Kai Ming Ting | DeepAI

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84 publications
Zhi-Hua Zhou
77 publications
Gang Li
67 publications
Flora D. Salim
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Ye Zhu
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Yuan Jin
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Sunil Aryal
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Takashi Washio
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Mark Carman
9 publications

∙ 01/01/2023

A principled distributional approach to trajectory similarity measurement

Existing measures and representations for trajectories have two longstan...

0 Yufan Wang, et al. ∙

∙ 12/30/2022

Detecting Change Intervals with Isolation Distributional Kernel

Detecting abrupt changes in data distribution is one of the most signifi...

0 Yang Cao, et al. ∙

∙ 09/29/2021

Breaking the curse of dimensionality with Isolation Kernel

The curse of dimensionality has been studied in different aspects. Howev...

0 Kai Ming Ting, et al. ∙

∙ 10/12/2020

The Impact of Isolation Kernel on Agglomerative Hierarchical Clustering Algorithms

Agglomerative hierarchical clustering (AHC) is one of the popular cluste...

0 Xin Han, et al. ∙

∙ 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...

4 Kai Ming Ting, et al. ∙

∙ 05/06/2020

A Comprehensive Survey on Outlying Aspect Mining Methods

In recent years, researchers have become increasingly interested in outl...

0 Durgesh Samariya, et al. ∙

∙ 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)...

0 Durgesh Samariya, et al. ∙

∙ 02/14/2020

Clustering based on Point-Set Kernel

Measuring similarity between two objects is the core operation in existi...

0 Kai Ming Ting, et al. ∙

∙ 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...

0 Kai Ming Ting, et al. ∙

∙ 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...

0 Xiaoyu Qin, et al. ∙

∙ 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...

0 Ye Zhu, et al. ∙

∙ 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...

0 Sunil Aryal, et al. ∙

∙ 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...

0 Ye Zhu, et al. ∙

∙ 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...

0 Ye Zhu, et al. ∙

∙ 07/03/2017

A simple efficient density estimator that enables fast systematic search

This paper introduces a simple and efficient density estimator that enab...

0 Jonathan R. Wells, et al. ∙

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