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» Structured metric learning for high dimensional problems
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KDD
2004
ACM
216views Data Mining» more  KDD 2004»
14 years 8 months ago
GPCA: an efficient dimension reduction scheme for image compression and retrieval
Recent years have witnessed a dramatic increase in the quantity of image data collected, due to advances in fields such as medical imaging, reconnaissance, surveillance, astronomy...
Jieping Ye, Ravi Janardan, Qi Li
COMPGEOM
2011
ACM
12 years 11 months ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
EMMCVPR
2007
Springer
14 years 1 months ago
Compositional Object Recognition, Segmentation, and Tracking in Video
Abstract. The complexity of visual representations is substantially limited by the compositional nature of our visual world which, therefore, renders learning structured object mod...
Björn Ommer, Joachim M. Buhmann
CVPR
2006
IEEE
14 years 9 months ago
AnnoSearch: Image Auto-Annotation by Search
Although it has been studied for several years by computer vision and machine learning communities, image annotation is still far from practical. In this paper, we present AnnoSea...
Xin-Jing Wang, Lei Zhang, Feng Jing, Wei-Ying Ma
ICPR
2006
IEEE
14 years 8 months ago
Competitive Mixtures of Simple Neurons
We propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. Our classifier includes a prior for the weights between different n...
Karthik Sridharan, Matthew J. Beal, Venu Govindara...