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» Iterative Learning Control - Monotonicity and Optimization
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NIPS
2004
15 years 4 months ago
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model
We derive an optimal learning rule in the sense of mutual information maximization for a spiking neuron model. Under the assumption of small fluctuations of the input, we find a s...
Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aiha...
ICASSP
2011
IEEE
14 years 6 months ago
Defining the controlling parameter in constrained discriminative linear transform for supervised speaker adaptation
Constrained discriminative linear transform (CDLT) optimized with Extended Baum-Welch (EBW) has been presented in the literature as a discriminative speaker adaptation method that...
Danning Jiang, Dimitri Kanevsky, Emmanuel Yashchin...
ESANN
2001
15 years 4 months ago
Learning fault-tolerance in Radial Basis Function Networks
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
Xavier Parra, Andreu Català
IJON
2008
133views more  IJON 2008»
15 years 1 months ago
A multi-objective approach to RBF network learning
The problem of inductive supervised learning is discussed in this paper within the context of multi-objective (MOBJ) optimization. The smoothness-based apparent (effective) comple...
Illya Kokshenev, Antônio de Pádua Bra...
NIPS
2007
15 years 4 months ago
Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion
We consider apprenticeship learning—learning from expert demonstrations—in the setting of large, complex domains. Past work in apprenticeship learning requires that the expert...
J. Zico Kolter, Pieter Abbeel, Andrew Y. Ng