Your selections:
A comparative study of practical stochastic clustering method with traditional methods
- Tan, Swee, Ting, Kaiming, Teng, Shyh
A generic ensemble approach to estimate multidimensional likelihood in Bayesian classifier learning
Boosting support vector machines successfully
Building sparse support vector machines for multi-instance classification
- Fu, Zhouyu, Lu, Guojun, Ting, Kaiming, Zhang, Dengsheng
Clustering gene expression data using ant-based heuristics
- Tan, Swee, Ting, Kaiming, Teng, Shyh
Data-dependent dissimilarity measure : An effective alternative to geometric distance measures
- Aryal, Sunil, Ting, Kaiming, Washio, Takashi, Haffari, Gholamreza
Defying the gravity of learning curve : A characteristic of nearest neighbour anomaly detectors
- Ting, Kaiming, Washio, Takashi, Wells, Jonathan, Aryal, Sunil
DEMass: a new density estimator for big data
- Ting, Kaiming, Washio, Takashi, Wells, Jonathan, Liu, Fei, Aryal, Sunil
Density estimation based on mass
- Ting, Kaiming, Washio, Takashi, Wells, Jonathan, Liu, Fei
Density-ratio based clustering for discovering clusters with varying densities
- Zhu, Ye, Ting, Kaiming, Carman, Mark
Efficient nonlinear classification via low-rank regularised least squares
- Fu, Zhouyu, Lu, Guojun, Ting, Kaiming, Zhang, Dengsheng
FaSS : Ensembles for stable learners
- Ting, Kaiming, Wells, Jonathan, Tan, Swee, Teng, Shyh, Webb, Geoffrey
Fast anomaly detection for streaming data
- Tan, Swee, Ting, Kaiming, Liu, Fei
Feature-subspace aggregating: ensembles for stable and unstable learners
- Ting, Kaiming, Wells, Jonathan, Tan, Swee, Teng, Shyh, Webb, Geoffrey
Grouping points by shared subspaces for effective subspace clustering
- Zhu, Ye, Ting, Kaiming, Carman, Mark
Half-space mass : a maximally robust and efficient data depth method
- Chen, Bo, Ting, Kaiming, Washio, Takashi, Haffari, Gholamreza
- Liu, Fei, Ting, Kaiming, Zhou, Zhi-Hua
Isolation-based anomaly detection using nearest-neighbor ensembles
- Bandaragoda, Tharindu, Ting, Kaiming, Albrecht, David, Liu, Fei, Zhu, Ye, Wells, Jonathan
Issues of grid-cluster retrievals in swarm-based clustering
- Tan, Swee, Ting, Kaiming, Teng, Shyh
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