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» Learning Probabilistic Models of Relational Structure
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IJCAI
2007
15 years 2 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
80
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ICALT
2005
IEEE
15 years 6 months ago
Flexible and Exploratory Learning by Polyscopic Topic Maps
Flexible and active education calls for a comprehensive restructuring of the traditional university course format. Such restructuring can be done in a natural and coherent way by ...
Dino Karabeg, Rolf Guescini, Tommy W. Nordeng
87
Voted
MICCAI
2006
Springer
16 years 1 months ago
Logarithm Odds Maps for Shape Representation
The concept of the Logarithm of the Odds (LogOdds) is frequently used in areas such as artificial neural networks, economics, and biology. Here, we utilize LogOdds for a shape repr...
Kilian M. Pohl, John W. Fisher III, Martha Elizabe...
CORR
2010
Springer
116views Education» more  CORR 2010»
14 years 7 months ago
Mixed-Membership Stochastic Block-Models for Transactional Networks
Abstract: Transactional network data can be thought of as a list of oneto-many communications (e.g., email) between nodes in a social network. Most social network models convert th...
Mahdi Shafiei, Hugh Chipman
AAAI
2010
15 years 2 months ago
Recognizing Multi-Agent Activities from GPS Data
Recent research has shown that surprisingly rich models of human behavior can be learned from GPS (positional) data. However, most research to date has concentrated on modeling si...
Adam Sadilek, Henry A. Kautz