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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 9 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
ICPR
2006
IEEE
14 years 10 months ago
Object and Scene Classification: what does a Supervised Approach Provide us?
Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurre...
Anna Bosch, Arnau Oliver, Robert Marti, Xavier Mu&...
ICDE
2008
IEEE
141views Database» more  ICDE 2008»
14 years 10 months ago
SPOT: A System for Detecting Projected Outliers From High-dimensional Data Streams
In this paper, we present a new technique, called Stream Projected Ouliter deTector (SPOT), to deal with outlier detection problem in high-dimensional data streams. SPOT is unique ...
Ji Zhang, Qigang Gao, Hai H. Wang
ICDM
2010
IEEE
193views Data Mining» more  ICDM 2010»
13 years 6 months ago
Supervised Link Prediction Using Multiple Sources
Link prediction is a fundamental problem in social network analysis and modern-day commercial applications such as Facebook and Myspace. Most existing research approaches this pro...
Zhengdong Lu, Berkant Savas, Wei Tang, Inderjit S....
CVPR
2007
IEEE
14 years 11 months ago
On-line Simultaneous Learning and Tracking of Visual Feature Graphs
Model learning and tracking are two important topics in computer vision. While there are many applications where one of them is used to support the other, there are currently only...
Arnaud Declercq, Justus H. Piater