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ICML
2009
IEEE
14 years 8 months ago
Learning Markov logic network structure via hypergraph lifting
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Stanley Kok, Pedro Domingos
PAMI
2008
196views more  PAMI 2008»
13 years 7 months ago
Distance Learning for Similarity Estimation
In this paper, we present a general guideline to find a better distance measure for similarity estimation based on statistical analysis of distribution models and distance function...
Jie Yu, Jaume Amores, Nicu Sebe, Petia Radeva, Qi ...
EELC
2006
126views Languages» more  EELC 2006»
13 years 11 months ago
Cross-Situational Learning: A Mathematical Approach
Abstract. We present a mathematical model of cross-situational learning, in which we quantify the learnability of words and vocabularies. We find that high levels of uncertainty ar...
Kenny Smith, Andrew D. M. Smith, Richard A. Blythe...
MC
2008
137views Computer Science» more  MC 2008»
13 years 9 months ago
Between 'Instructions' and 'Diy': Tagging in Learning Communities
In this paper, we discuss the novel technology tagging and the results of analyzing a learning community in a popular system that relies on tagging namely YouTube. We present our ...
Milena Reichel, Heidi Schelhowe
SLOGICA
2008
120views more  SLOGICA 2008»
13 years 7 months ago
Emergence of Information Transfer by Inductive Learning
We study a simple game theoretic model of information transfer which we consider to be a baseline model for capturing strategic aspects of epistemological questions. In particular,...
Simon M. Huttegger, Brian Skyrms