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CORR
2011
Springer
182views Education» more  CORR 2011»
12 years 8 months ago
Adaptively Learning the Crowd Kernel
We introduce an algorithm that, given n objects, learns a similarity matrix over all n2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen t...
Omer Tamuz, Ce Liu, Serge Belongie, Ohad Shamir, A...
ICDM
2006
IEEE
225views Data Mining» more  ICDM 2006»
13 years 10 months ago
Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
AVSS
2009
IEEE
13 years 5 months ago
Robust Vehicle Detection for Tracking in Highway Surveillance Videos Using Unsupervised Learning
This paper presents a novel approach to vehicle detection in highway surveillance videos. This method incorporates well-studied computer vision and machine learning techniques to ...
Birgi Tamersoy, Jake K. Aggarwal
ICCV
2009
IEEE
13 years 2 months ago
Bayesian Poisson regression for crowd counting
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
Antoni B. Chan, Nuno Vasconcelos
NCA
2008
IEEE
13 years 4 months ago
Polynomial kernel adaptation and extensions to the SVM classifier learning
Three extensions to the Kernel-AdaTron training algorithm for Support Vector Machine classifier learning are presented. These extensions allow the trained classifier to adhere more...
Ramy Saad, Saman K. Halgamuge, Jason Li