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» Learning Compressible Models
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CVPR
2003
IEEE
16 years 6 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
134
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IADIS
2004
15 years 5 months ago
Modelling Inductive Reasoning Ability for Adaptive Virtual Learning Environment
Inductive reasoning is one of the important characteristics of human intelligence. Researchers have regarded inductive reasoning as one of the seven primary mental abilities that ...
Taiyu Lin, Kinshuk, Paul McNab
CORR
2010
Springer
151views Education» more  CORR 2010»
15 years 4 months ago
The Challenge of Believability in Video Games: Definitions, Agents Models and Imitation Learning
In this paper, we address the problem of creating believable agents (virtual characters) in video games. We consider only one meaning of believability, "giving the feeling of...
Fabien Tencé, Cédric Buche, Pierre D...
ML
2008
ACM
150views Machine Learning» more  ML 2008»
15 years 3 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
173
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ISOLA
2010
Springer
15 years 2 months ago
LivingKnowledge: Kernel Methods for Relational Learning and Semantic Modeling
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...
Alessandro Moschitti