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NN
2002
Springer
136views Neural Networks» more  NN 2002»
15 years 5 months ago
Bayesian model search for mixture models based on optimizing variational bounds
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Naonori Ueda, Zoubin Ghahramani
NPL
2006
172views more  NPL 2006»
15 years 5 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
15 years 10 months ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
STOC
1993
ACM
141views Algorithms» more  STOC 1993»
15 years 10 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
IPMU
2010
Springer
15 years 9 months ago
Credal Sets Approximation by Lower Probabilities: Application to Credal Networks
Abstract. Credal sets are closed convex sets of probability mass functions. The lower probabilities specified by a credal set for each element of the power set can be used as cons...
Alessandro Antonucci, Fabio Cuzzolin