2011
ACML
ACML 2011
Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization
Abstract
In this paper, we address the problem of non-parametric density estimation on a set of strings $\Sigma^*$. We introduce a probabilistic model - called quadratic weighted automaton, or QWA - and we present some methods which can be used in a density estimation task. A spectral analysis method leads to an effective regularization and a consistent estimate of the parameters. We provide a set of theoretical results on the convergence of this method. Experiments show that the combination of this method with likelihood maximization may be an interesting alternative to the well-known Baum-Welch algorithm.
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Interdisciplinary Bridge
— Machine Learning and Mathematics & Optimization
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Trend Setter
— Discrete Mathematics
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Keyword Pioneer
— spectral algorithm
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing
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Hot Topic Early Bird
— density estimation
Authors
Topics
Machine Learning > Optimization & Theory > Optimization
Machine Learning > Optimization & Theory > Statistical Learning
Mathematics & Optimization > Mathematics > Discrete Mathematics
Machine Learning > Bayesian & Probabilistic > Probabilistic Modeling
Machine Learning > Core Methods > Probabilistic Modeling