566 search results - page 97 / 114 » Approximation Spaces in Machine Learning and Pattern Recogni... |
94
Voted
ICCV
2007
IEEE
15 years 6 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
130
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HUC
2011
Springer
13 years 11 months ago
2011
Springer
Sensor-enabled smartphones are opening a new frontier in the development of mobile sensing applications. The recognition of human activities and context from sensor-data using cla...
98
Voted
CVPR
2007
IEEE
16 years 1 months ago
2007
IEEE
Kernel methods have been widely studied in the field of pattern recognition. These methods implicitly map, "the kernel trick," the data into a space which is more approp...
KDD
2010
ACM
15 years 1 months ago
2010
ACM
In plenty of scenarios, data can be represented as vectors mathematically abstracted as points in a Euclidean space. Because a great number of machine learning and data mining app...
100
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KDD
2006
ACM
16 years 4 days ago
2006
ACM
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...