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» Learning Complex Concepts Using Crowdsourcing: A Bayesian Ap...
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AI
2010
Springer
13 years 7 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel
IJCAI
1989
13 years 8 months ago
A Critique of the Valiant Model
This paper considers the Valiant framework as it is applied to the task of learning logical concepts from random examples. It is argued that the current interpretation of this Val...
Wray L. Buntine
ICML
2009
IEEE
14 years 8 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
SG
2007
Springer
14 years 1 months ago
Correlating Text and Images: Concept and Evaluation
This paper presents the concept and an evaluation of a novel approach to support students to understand complex spatial relations and to learn unknown terms of a domain-specific t...
Timo Götzelmann, Pere-Pau Vázquez, Knu...
EUROCOLT
1995
Springer
13 years 11 months ago
The structure of intrinsic complexity of learning
Limiting identification of r.e. indexes for r.e. languages (from a presentation of elements of the language) and limiting identification of programs for computable functions (fr...
Sanjay Jain, Arun Sharma