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» Learning of Boolean Functions Using Support Vector Machines
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EMNLP
2004
13 years 10 months ago
Max-Margin Parsing
We present a novel discriminative approach to parsing inspired by the large-margin criterion underlying support vector machines. Our formulation uses a factorization analogous to ...
Ben Taskar, Dan Klein, Mike Collins, Daphne Koller...
TOG
2008
98views more  TOG 2008»
13 years 9 months ago
Upright orientation of man-made objects
Humans usually associate an upright orientation with objects, placing them in a way that they are most commonly seen in our surroundings. While it is an open challenge to recover ...
Hongbo Fu, Daniel Cohen-Or, Gideon Dror, Alla Shef...
ICCV
2011
IEEE
12 years 9 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
PRL
2010
159views more  PRL 2010»
13 years 7 months ago
Creating diverse nearest-neighbour ensembles using simultaneous metaheuristic feature selection
The nearest-neighbour (1NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. A vital consideration in obtaining good res...
Muhammad Atif Tahir, Jim E. Smith
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 9 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...