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» Information Theory, Inference, and Learning Algorithms
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JMLR
2010
119views more  JMLR 2010»
14 years 11 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
155
Voted
AI
2007
Springer
15 years 11 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
15 years 10 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
15 years 9 months 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
152
Voted
NN
2006
Springer
141views Neural Networks» more  NN 2006»
15 years 5 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