Kai Ming Ting
Orcid: 0000-0001-7892-6194Affiliations:
- Nanjing University, National Key Laboratory for Novel Software Technology, Nanjing, China
According to our database1,
Kai Ming Ting
authored at least 151 papers
between 1994 and 2024.
Collaborative distances:
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Bibliography
2024
A Principled Distributional Approach to Trajectory Similarity Measurement and its Application to Anomaly Detection.
J. Artif. Intell. Res., 2024
J. Artif. Intell. Res., 2024
2023
Pattern Recognit., July, 2023
IEEE Trans. Knowl. Data Eng., March, 2023
CoRR, 2023
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the IEEE International Conference on Data Mining, 2023
2022
Spectral-Spatial Anomaly Detection of Hyperspectral Data Based on Improved Isolation Forest.
IEEE Trans. Geosci. Remote. Sens., 2022
A New Distributional Treatment for Time Series and An Anomaly Detection Investigation.
Proc. VLDB Endow., 2022
Hierarchical clustering that takes advantage of both density-peak and density-connectivity.
Inf. Syst., 2022
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel (Extended Abstract).
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
2021
CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities.
Pattern Recognit., 2021
Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel.
J. Artif. Intell. Res., 2021
Isolation kernel: the X factor in efficient and effective large scale online kernel learning.
Data Min. Knowl. Discov., 2021
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021
Proceedings of the IEEE International Conference on Data Mining, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Simple supervised dissimilarity measure: Bolstering iForest-induced similarity with class information without learning.
Knowl. Inf. Syst., 2020
A comparative study of data-dependent approaches without learning in measuring similarities of data objects.
Data Min. Knowl. Discov., 2020
CoRR, 2020
Proceedings of the Web Information Systems Engineering - WISE 2020, 2020
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
2019
Pattern Recognit. Lett., 2019
Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms.
Mach. Learn., 2019
Improving Stochastic Neighbour Embedding fundamentally with a well-defined data-dependent kernel.
CoRR, 2019
A new simple and effective measure for bag-of-word inter-document similarity measurement.
CoRR, 2019
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Nearest Neighbor Ensembles: An Effective Method for Difficult Problems in Streaming Classification with Emerging New Classes.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019
Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
NII Shonan Meet. Rep., 2018
Pattern Recognit., 2018
Mach. Learn., 2018
CoRR, 2018
Comput. Intell., 2018
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Proceedings of the IEEE International Conference on Data Mining, 2018
Proceedings of the IEEE International Conference on Data Mining, 2018
2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Classification Under Streaming Emerging New Classes: A Solution Using Completely-Random Trees.
IEEE Trans. Knowl. Data Eng., 2017
Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors.
Mach. Learn., 2017
Data-dependent dissimilarity measure: an effective alternative to geometric distance measures.
Knowl. Inf. Syst., 2017
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
Pattern Recognit., 2016
Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems.
Mach. Learn., 2016
ZERO++: Harnessing the Power of Zero Appearances to Detect Anomalies in Large-Scale Data Sets.
J. Artif. Intell. Res., 2016
A Generic Ensemble Approach to Estimate Multidimensional Likelihood in Bayesian Classifier Learning.
Comput. Intell., 2016
Revisiting Attribute Independence Assumption in Probabilistic Unsupervised Anomaly Detection.
Proceedings of the Intelligence and Security Informatics - 11th Pacific Asia Workshop, 2016
Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016
2015
Mach. Learn., 2015
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015
Proceedings of the Information Retrieval Technology, 2015
2014
Pattern Recognit., 2014
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2014
Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014
2013
IEEE Trans. Neural Networks Learn. Syst., 2013
Neural Comput. Appl., 2013
Comput. Intell., 2013
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013
Proceedings of the IJCAI 2013, 2013
2012
Pattern Recognit., 2012
Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification.
Mach. Learn., 2012
Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012
Proceedings of the Tenth Australasian Data Mining Conference, AusDM 2012, Sydney, 2012
2011
IEEE Trans. Multim., 2011
Proceedings of the International Conference on Computational Science, 2011
Pattern Recognit., 2011
Mach. Learn., 2011
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011
Proceedings of the Neural Information Processing - 18th International Conference, 2011
Proceedings of the 11th IEEE International Conference on Data Mining, 2011
2010
Proceedings of the Encyclopedia of Machine Learning, 2010
Best papers from the 12th Pacific-Asia conference on knowledge discovery and data mining (PAKDD2008).
Knowl. Inf. Syst., 2010
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010
Proceedings of the 20th International Conference on Pattern Recognition, 2010
Proceedings of the ICDM 2010, 2010
A Comparative Study of a Practical Stochastic Clustering Method with Traditional Methods.
Proceedings of the AI 2010: Advances in Artificial Intelligence, 2010
2009
Proceedings of the Multiple Classifier Systems, 8th International Workshop, 2009
Proceedings of the Multiple Classifier Systems, 8th International Workshop, 2009
2008
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008
Proceedings of the IEEE Congress on Evolutionary Computation, 2008
2007
To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators.
IEEE Trans. Knowl. Data Eng., 2007
Classifying under computational resource constraints: anytime classification using probabilistic estimators.
Mach. Learn., 2007
Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007
Proceedings of the Progress in Artificial Life, Third Australian Conference, 2007
2006
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2006
To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles.
Proceedings of the Machine Learning: ECML 2006, 2006
Proceedings of the IEEE International Conference on Evolutionary Computation, 2006
Proceedings of the AI 2006: Advances in Artificial Intelligence, 2006
Ehipasiko: A Content-based Image Indexing and Retrieval System.
Proceedings of the Advances in Intelligent IT, 2006
2005
On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions.
Mach. Learn., 2005
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2005
Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005
2004
Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees.
Proceedings of the Machine Learning: ECML 2004, 2004
Improving the Centered CUSUMS Statistic for Structural Break Detection in Time Series.
Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004
2003
Comput. Intell., 2003
Model Stability: A key factor in determining whether an algorithm produces an optimal model from a matching distribution.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003
2002
IEEE Trans. Knowl. Data Eng., 2002
Issues in Classifier Evaluation using Optimal Cost Curves.
Proceedings of the Machine Learning, 2002
Proceedings of the Discovery Science, 5th International Conference, 2002
2000
A Comparative Study of Cost-Sensitive Boosting Algorithms.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000
Proceedings of the Machine Learning: ECML 2000, 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May 31, 2000
1999
Knowl. Inf. Syst., 1999
Proceedings of the Methodologies for Knowledge Discovery and Data Mining, 1999
Proceedings of the International Joint Conference Neural Networks, 1999
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees.
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999
1998
Proceedings of the Principles of Data Mining and Knowledge Discovery, 1998
Integrating boosting and stochastic attribute selection committees for further improving the performance of decision tree learning.
Proceedings of the Tenth IEEE International Conference on Tools with Artificial Intelligence, 1998
Proceedings of the Machine Learning: ECML-98, 1998
1997
Intell. Data Anal., 1997
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997
Stacking Bagged and Dagged Models.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997
Proceedings of the Machine Learning: ECML-97, 1997
1996
The Characterisation of Predictive Accuracy and Decision Combination.
Proceedings of the Machine Learning, 1996
1995
Proceedings of the Case-Based Reasoning Research and Development, 1995
1994
An M-of-N Rule Induction Algorithm and its Application to DNA Domain.
Proceedings of the 27th Annual Hawaii International Conference on System Sciences (HICSS-27), 1994