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EMNLP
2010
15 years 4 months ago
A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension
Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corp...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...
ICDM
2009
IEEE
200views Data Mining» more  ICDM 2009»
15 years 4 months ago
Improving SVM Classification on Imbalanced Data Sets in Distance Spaces
Abstract--Imbalanced data sets present a particular challenge to the data mining community. Often, it is the rare event that is of interest and the cost of misclassifying the rare ...
Suzan Koknar-Tezel, Longin Jan Latecki
IDA
2009
Springer
15 years 4 months ago
Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases
We propose a method for trajectory classification based on trajectory voting in Moving Object Databases (MOD). Trajectory voting is performed based on local trajectory similarity. ...
Costas Panagiotakis, Nikos Pelekis, Ioannis Kopana...
CVPR
2006
IEEE
16 years 8 months ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman
ICCV
2005
IEEE
16 years 8 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu