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TNN
2008
82views more  TNN 2008»
14 years 9 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 ...
WSC
2007
14 years 12 months ago
Estimating the probability of a rare event over a finite time horizon
We study an approximation for the zero-variance change of measure to estimate the probability of a rare event in a continuous-time Markov chain. The rare event occurs when the cha...
Pieter-Tjerk de Boer, Pierre L'Ecuyer, Gerardo Rub...
IPSN
2004
Springer
15 years 3 months ago
Locally constructed algorithms for distributed computations in ad-hoc networks
In this paper we develop algorithms for distributed computation of a broad range of estimation and detection tasks over networks with arbitrary but fixed connectivity. The distri...
Dzulkifli S. Scherber, Haralabos C. Papadopoulos
ICML
2005
IEEE
15 years 10 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
87
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ICASSP
2010
IEEE
14 years 9 months ago
Large margin estimation of n-gram language models for speech recognition via linear programming
We present a novel discriminative training algorithm for n-gram language models for use in large vocabulary continuous speech recognition. The algorithm uses large margin estimati...
Vladimir Magdin, Hui Jiang