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» Learning Low-Level Vision
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NIPS
1998
15 years 4 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
155
Voted
PRICAI
2010
Springer
15 years 1 months ago
Towards Artificial Systems: What Can We Learn from Human Perception?
Research in learning algorithms and sensor hardware has led to rapid advances in artificial systems over the past decade. However, their performance continues to fall short of the ...
Heinrich H. Bülthoff, Lewis L. Chuang
112
Voted
IROS
2006
IEEE
120views Robotics» more  IROS 2006»
15 years 8 months ago
Learning from Nature to Build Intelligent Autonomous Robots
Information processing within autonomous robots should follow a biomimetic approach. In contrast to traditional approaches that make intensive use of accurate measurements, numeric...
Rainer Bischoff 0002, Volker Graefe
120
Voted
CAISE
2004
Springer
15 years 8 months ago
A knowledge-based approach to ontology learning and semantic annotation
The so-called Semantic Web vision will certainly benefit from automatic semantic annotation of words in documents. We present a method, called structural semantic interconnections ...
Roberto Navigli, Paola Velardi
105
Voted
ICVS
2003
Springer
15 years 7 months ago
A Spectral Approach to Learning Structural Variations in Graphs
This paper shows how to construct a linear deformable model for graph structure by performing principal components analysis (PCA) on the vectorised adjacency matrix. We commence b...
Bin Luo, Richard C. Wilson, Edwin R. Hancock