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KDD
1999
ACM
199views Data Mining» more  KDD 1999»
15 years 6 months ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang
127
Voted
IPMI
2007
Springer
16 years 3 months ago
Shape Regression Machine
Abstract. We present a machine learning approach called shape regression machine (SRM) to segmenting in real time an anatomic structure that manifests a deformable shape in a medic...
Shaohua Kevin Zhou, Dorin Comaniciu
ICML
2006
IEEE
15 years 8 months ago
Multiclass reduced-set support vector machines
There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduce...
Benyang Tang, Dominic Mazzoni
ICCV
2007
IEEE
16 years 4 months ago
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
ICMLA
2010
15 years 6 days ago
A New Approach to Classification with the Least Number of Features
Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separati...
Sascha Klement, Thomas Martinetz