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» Learning with Kernels and Logical Representations
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AISC
2008
Springer
15 years 2 months ago
Extending Graphical Representations for Compact Closed Categories with Applications to Symbolic Quantum Computation
Graph-based formalisms of quantum computation provide an abstract and symbolic way to represent and simulate computations. However, manual manipulation of such graphs is slow and e...
Lucas Dixon, Ross Duncan
ICIP
2009
IEEE
16 years 1 months ago
Spatio-temporal Tube Kernel For Actor Retrieval
This paper presents an actor video retrieval system based on face video-tubes extraction and representation with sets of temporally coherent features. Visual features, SIFT points...
101
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COLING
2000
15 years 1 months ago
Learning Semantic-Level Information Extraction Rules by Type-Oriented ILP
This paper describes an approach to using semantic rcprcsentations for learning information extraction (IE) rules by a type-oriented inductire logic programming (ILl)) system. NLP...
Yutaka Sasaki, Yoshihiro Matsuo
ICCV
2003
IEEE
16 years 2 months ago
Recognition with Local Features: the Kernel Recipe
Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have be...
Christian Wallraven, Barbara Caputo, Arnulf B. A. ...
ECCV
2004
Springer
16 years 2 months ago
Multiple View Feature Descriptors from Image Sequences via Kernel Principal Component Analysis
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
Jason Meltzer, Ming-Hsuan Yang, Rakesh Gupta, Stef...