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» Pruning Training Sets for Learning of Object Categories
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ACL
2009
13 years 7 months ago
Better Word Alignments with Supervised ITG Models
This work investigates supervised word alignment methods that exploit inversion transduction grammar (ITG) constraints. We consider maximum margin and conditional likelihood objec...
Aria Haghighi, John Blitzer, John DeNero, Dan Klei...
DAGM
2007
Springer
14 years 1 months ago
Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification
Cascades of classifiers constitute an important architecture for fast object detection. While boosting of simple (weak) classifiers provides an established framework, the design of...
Rezaul Karim, Martin Bergtholdt, Jörg H. Kapp...
SIGMOD
2010
ACM
262views Database» more  SIGMOD 2010»
14 years 1 months ago
K-nearest neighbor search for fuzzy objects
The K-Nearest Neighbor search (kNN) problem has been investigated extensively in the past due to its broad range of applications. In this paper we study this problem in the contex...
Kai Zheng, Gabriel Pui Cheong Fung, Xiaofang Zhou
CVPR
2010
IEEE
14 years 2 months ago
YouTubeCat: Learning to Categorize Wild Web Videos
Automatic categorization of videos in a Web-scale unconstrained collection such as YouTube is a challenging task. A key issue is how to build an effective training set in the pres...
Zheshen Wang, Ming Zhao, Yang Song, Sanjiv Kumar, ...
NIPS
2007
13 years 10 months ago
Agreement-Based Learning
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
Percy Liang, Dan Klein, Michael I. Jordan