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ICML
1999
IEEE
16 years 17 days ago
Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...
Rajesh Parekh, Vasant Honavar
ICCV
2011
IEEE
13 years 11 months ago
Discriminative Figure-Centric Models for Joint Action Localization and Recognition
In this paper we develop an algorithm for action recognition and localization in videos. The algorithm uses a figurecentric visual word representation. Different from previous ap...
Tian Lan, Yang Wang, Greg Mori
LATA
2010
Springer
15 years 6 months ago
Three Learnable Models for the Description of Language
Abstract. Learnability is a vital property of formal grammars: representation classes should be defined in such a way that they are learnable. One way to build learnable represent...
Alexander Clark
IJCV
2007
163views more  IJCV 2007»
14 years 11 months ago
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
In this paper, we present a novel image representation that renders it possible to access natural scenes by local semantic description. Our work is motivated by the continuing effo...
Julia Vogel, Bernt Schiele
81
Voted
CVPR
2010
IEEE
15 years 8 months ago
Hierarchical Convolutional Sparse Image Decomposition
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew Zeiler, Dilip Krishnan, Graham Taylor, Rob...