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» Information Theory, Inference, and Learning Algorithms
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JMLR
2010
119views more  JMLR 2010»
13 years 2 months ago
Semi-Supervised Learning via Generalized Maximum Entropy
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
Ayse Erkan, Yasemin Altun
AI
2007
Springer
14 years 2 months ago
Learning Network Topology from Simple Sensor Data
In this paper, we present an approach for recovering a topological map of the environment using only detection events from a deployed sensor network. Unlike other solutions to this...
Dimitri Marinakis, Philippe Giguère, Gregor...
OTM
2005
Springer
14 years 1 months ago
OWL-Based User Preference and Behavior Routine Ontology for Ubiquitous System
In ubiquitous computing, behavior routine learning is the process of mining the context-aware data to find interesting rules on the user’s behavior, while preference learning tri...
Kim Anh Pham Ngoc, Young-Koo Lee, Sungyoung Lee
ICGI
1994
Springer
14 years 1 days ago
Computer Assisted Grammar Construction
: This paper proposes a new inference approach for Chinese probabilistic context-free grammar, which implements the EM algorithm based on the bracket matching schemes. By utilizing...
S. J. Young, H.-H. Shih
NN
2006
Springer
141views Neural Networks» more  NN 2006»
13 years 7 months ago
Encoding uncertainty in the hippocampus
The medial temporal lobe may play a critical role in binding successive events into memory while encoding contextual information in implicit and explicit memory tasks. Information...
Lee M. Harrison, Andrew Duggins, Karl J. Friston