Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization

Raphael Bailly
; Proceedings of the Asian Conference on Machine Learning, PMLR 20:147-163, 2011.

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.

Cite this Paper


BibTeX
@InProceedings{pmlr-v20-bailly11, title = {Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization}, author = {Raphael Bailly}, booktitle = {Proceedings of the Asian Conference on Machine Learning}, pages = {147--163}, year = {2011}, editor = {Chun-Nan Hsu and Wee Sun Lee}, volume = {20}, series = {Proceedings of Machine Learning Research}, address = {South Garden Hotels and Resorts, Taoyuan, Taiwain}, month = {14--15 Nov}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v20/bailly11/bailly11.pdf}, url = {http://proceedings.mlr.press/v20/bailly11.html}, 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.} }
Endnote
%0 Conference Paper %T Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization %A Raphael Bailly %B Proceedings of the Asian Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2011 %E Chun-Nan Hsu %E Wee Sun Lee %F pmlr-v20-bailly11 %I PMLR %J Proceedings of Machine Learning Research %P 147--163 %U http://proceedings.mlr.press %V 20 %W PMLR %X 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.
RIS
TY - CPAPER TI - Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization AU - Raphael Bailly BT - Proceedings of the Asian Conference on Machine Learning PY - 2011/11/17 DA - 2011/11/17 ED - Chun-Nan Hsu ED - Wee Sun Lee ID - pmlr-v20-bailly11 PB - PMLR SP - 147 DP - PMLR EP - 163 L1 - http://proceedings.mlr.press/v20/bailly11/bailly11.pdf UR - http://proceedings.mlr.press/v20/bailly11.html AB - 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. ER -
APA
Bailly, R.. (2011). Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization. Proceedings of the Asian Conference on Machine Learning, in PMLR 20:147-163

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