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» Learning on the Test Data: Leveraging Unseen Features
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WSDM
2012
ACM
300views Data Mining» more  WSDM 2012»
12 years 4 months ago
Adding semantics to microblog posts
Microblogs have become an important source of information for the purpose of marketing, intelligence, and reputation management. Streams of microblogs are of great value because o...
Edgar Meij, Wouter Weerkamp, Maarten de Rijke
PSIVT
2009
Springer
400views Multimedia» more  PSIVT 2009»
14 years 3 months ago
Local Image Descriptors Using Supervised Kernel ICA
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
Masaki Yamazaki, Sidney Fels
CVPR
2007
IEEE
14 years 3 months ago
Moving Object Detection on a Runway Prior to Landing Using an Onboard Infrared Camera
Determining the status of a runway prior to landing is essential for any aircraft, whether manned or unmanned. In this paper, we present a method that can detect moving objects on...
Cheng-Hua Pai, Yuping Lin, Gérard G. Medion...
IJPRAI
2002
93views more  IJPRAI 2002»
13 years 8 months ago
Improving Stability of Decision Trees
Decision-tree algorithms are known to be unstable: small variations in the training set can result in different trees and different predictions for the same validation examples. B...
Mark Last, Oded Maimon, Einat Minkov
PAMI
2010
192views more  PAMI 2010»
13 years 7 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens