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ICASSP
2010
IEEE
15 years 7 months ago
Hierarchical dictionary learning for invariant classification
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
Leah Bar, Guillermo Sapiro
JMLR
2006
123views more  JMLR 2006»
15 years 6 months ago
Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies
In this paper, we propose a number of adaptive prototype learning (APL) algorithms. They employ the same algorithmic scheme to determine the number and location of prototypes, but...
Fu Chang, Chin-Chin Lin, Chi-Jen Lu
COLING
2002
15 years 6 months ago
Learning Question Classifiers
In order to respond correctly to a free form factual question given a large collection of texts, one needs to understand the question to a level that allows determining some of th...
Xin Li, Dan Roth
ICDAR
2011
IEEE
14 years 6 months ago
Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning
—Reading text from photographs is a challenging problem that has received a signicant amount of attention. Two key components of most systems are (i) text detection from images a...
Adam Coates, Blake Carpenter, Carl Case, Sanjeev S...
CVPR
2012
IEEE
13 years 9 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...