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EVOW
2009
Springer
16 years 1 months ago
Evolutionary Optimization Guided by Entropy-Based Discretization
The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Guleng Sheri, David W. Corne
PRL
2011
15 years 1 months ago
Object recognition using proportion-based prior information: Application to fisheries acoustics
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
Riwal Lefort, Ronan Fablet, Jean-Marc Boucher
JUCS
2010
159views more  JUCS 2010»
15 years 1 months ago
Authoring of Probabilistic Sequencing in Adaptive Hypermedia with Bayesian Networks
Abstract: One of the difficulties that self-directed learners face on their learning process is choosing the right learning resources. One of the goals of adaptive educational syst...
Sergio Gutiérrez Santos, Jaime Mayor-Berzal...
ICML
2007
IEEE
16 years 7 months ago
Restricted Boltzmann machines for collaborative filtering
Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class of two-layer undirected graphical models, called R...
Ruslan Salakhutdinov, Andriy Mnih, Geoffrey E. Hin...
ICML
2003
IEEE
15 years 12 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens