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NIPS
1998
13 years 10 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
ISIWI
2000
13 years 10 months ago
Automatic Document Classification - A thorough Evaluation of various Methods
(Automatic) document classification is generally defined as content-based assignment of one or more predefined categories to documents. Usually, machine learning, statistical patt...
Christoph Goller, J. Löning, T. Will, W. Wolf...
ICML
2007
IEEE
14 years 10 months ago
Dirichlet aggregation: unsupervised learning towards an optimal metric for proportional data
Proportional data (normalized histograms) have been frequently occurring in various areas, and they could be mathematically abstracted as points residing in a geometric simplex. A...
Hua-Yan Wang, Hongbin Zha, Hong Qin
GIS
2010
ACM
13 years 7 months ago
Bridge detection in grid terrains and improved drainage enforcement
Bare Earth gridded digital elevation models (DEMs) are often used to extract hydrologic features such as rivers and watersheds. DEMs must be conditioned by removing spurious sinks...
Ryan Carlson, Andrew Danner
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
13 years 10 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang