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» Learning and Inference with Constraints
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ICML
2010
IEEE
13 years 11 months ago
Multiagent Inductive Learning: an Argumentation-based Approach
Multiagent Inductive Learning is the problem that groups of agents face when they want to perform inductive learning, but the data of interest is distributed among them. This pape...
Santiago Ontañón, Enric Plaza
ICALT
2010
IEEE
13 years 8 months ago
Modelling Affect in Learning Environments - Motivation and Methods
Emotions have a functional relevance to learning and achievement. Not surprisingly then, affective diagnoses are an important aspect of expert human mentoring. Computerbased learni...
Shazia Afzal, Peter Robinson
UAI
2008
13 years 11 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
CP
1998
Springer
14 years 2 months ago
Optimizing with Constraints: A Case Study in Scheduling Maintenance of Electric Power Units
A well-studied problem in the electric power industry is that of optimally scheduling preventative maintenance of power generating units within a power plant. We show how these pr...
Daniel Frost, Rina Dechter
BMCBI
2008
98views more  BMCBI 2008»
13 years 10 months ago
GBNet: Deciphering regulatory rules in the co-regulated genes using a Gibbs sampler enhanced Bayesian network approach
Background: Combinatorial regulation of transcription factors (TFs) is important in determining the complex gene expression patterns particularly in higher organisms. Deciphering ...
Li Shen, Jie Liu, Wei Wang