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» Learning and using relational theories
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NIPS
2004
14 years 11 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
CE
2007
113views more  CE 2007»
14 years 10 months ago
Research and development of web-based virtual online classroom
To build a web-based virtual learning environment depends on information technologies, concerns technology supporting learning methods and theories. A web-based virtual online cla...
Zongkai Yang, Qingtang Liu
KR
2004
Springer
15 years 3 months ago
How to Interweave Knowledge about Object Structure and Concepts
This article presents a general framework for integrating reasoning about object structure and concept taxonomies. The structural relations in the domain of objects discussed are ...
Carola Eschenbach
VIS
2009
IEEE
399views Visualization» more  VIS 2009»
15 years 11 months ago
Visual Human+Machine Learning
In this paper we describe a novel method to integrate interactive visual analysis and machine learning to support the insight generation of the user. The suggested approach combine...
Raphael Fuchs, Jürgen Waser, Meister Eduard GrÃ...
ECML
2007
Springer
15 years 4 months ago
Scale-Space Based Weak Regressors for Boosting
Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based...
Jin Hyeong Park, Chandan K. Reddy