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AMAI
2004
Springer
15 years 12 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
ATAL
2008
Springer
15 years 8 months ago
Using adaptive consultation of experts to improve convergence rates in multiagent learning
In this paper we study the use of experts algorithms in a multiagent setting. In this paper we allow agents to use multiple experts and explore different experts algorithms that a...
Greg Hines, Kate Larson
ESANN
2007
15 years 8 months ago
Complexity bounds of radial basis functions and multi-objective learning
In the paper, the problem of multi-objective (MOBJ) learning is discussed. The problem of obtaining apparent (effective) complexity measure, which is one of the objectives, is con...
Illya Kokshenev, Antônio de Pádua Bra...
CORR
2010
Springer
73views Education» more  CORR 2010»
15 years 6 months ago
Exponential Family Hybrid Semi-Supervised Learning
We present an approach to semi-supervised learning based on an exponential family characterization. Our approach generalizes previous work on coupled priors for hybrid generative/...
Arvind Agarwal, Hal Daumé III
ESANN
2006
15 years 8 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...