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ICPR
2006
IEEE
14 years 8 months ago
Dimensionality Reduction with Adaptive Kernels
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
Shuicheng Yan, Xiaoou Tang
CVPR
2001
IEEE
14 years 9 months ago
Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images
We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...
IVC
2006
259views more  IVC 2006»
13 years 7 months ago
Object detection using spatial histogram features
In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, th...
Hongming Zhang, Wen Gao, Xilin Chen, Debin Zhao
ICML
2007
IEEE
14 years 8 months ago
On learning with dissimilarity functions
We study the problem of learning a classification task in which only a dissimilarity function of the objects is accessible. That is, data are not represented by feature vectors bu...
Liwei Wang, Cheng Yang, Jufu Feng
ICML
2005
IEEE
14 years 8 months ago
Naive Bayes models for probability estimation
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
Daniel Lowd, Pedro Domingos