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TNN
2008
82views more  TNN 2008»
15 years 6 months ago
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
Cristiano Cervellera, Danilo Macciò, Marco ...
EWRL
2008
15 years 8 months ago
Bayesian Reward Filtering
A wide variety of function approximation schemes have been applied to reinforcement learning. However, Bayesian filtering approaches, which have been shown efficient in other field...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
INTERSPEECH
2010
15 years 1 months ago
On generating combilex pronunciations via morphological analysis
Combilex is a high quality lexicon that has been developed specifically for speech technology purposes and recently released by CSTR. Combilex benefits from many advanced features...
Korin Richmond, Robert A. J. Clark, Susan Fitt
AUTOMATICA
2005
136views more  AUTOMATICA 2005»
15 years 6 months ago
Conjugate Lyapunov functions for saturated linear systems
Based on a recent duality theory for linear differential inclusions (LDIs), the condition for stability of an LDI in terms of one Lyapunov function can be easily derived from that...
Tingshu Hu, Rafal Goebel, Andrew R. Teel, Zongli L...
ALT
2004
Springer
16 years 3 months ago
Convergence of a Generalized Gradient Selection Approach for the Decomposition Method
The decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines. For a special c...
Nikolas List