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130
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ACL
2006
15 years 4 months ago
Unsupervised Relation Disambiguation Using Spectral Clustering
This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. I...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
110
Voted
ESANN
2003
15 years 4 months ago
Robust Topology Representing Networks
Martinetz and Schulten proposed the use of a Competitive Hebbian Learning (CHL) rule to build Topology Representing Networks. From a set of units and a data distribution, a link i...
Michaël Aupetit
128
Voted
ROBOCUP
2009
Springer
134views Robotics» more  ROBOCUP 2009»
15 years 10 months ago
Learning Complementary Multiagent Behaviors: A Case Study
As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
Shivaram Kalyanakrishnan, Peter Stone
163
Voted
ICIP
2010
IEEE
15 years 22 days ago
Automatic target recognition based on simultaneous sparse representation
In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extr...
Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellap...
IWANN
2005
Springer
15 years 9 months ago
Characterizing Self-developing Biological Neural Networks: A First Step Towards Their Application to Computing Systems
Carbon nanotubes are often seen as the only alternative technology to silicon transistors. While they are the most likely short-term alternative, other longer-term alternatives sho...
Hugues Berry, Olivier Temam