Hidden Markov Models Training Using Population-based Metaheuristics
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[1] Shumeet Baluja,et al. A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .
[2] Hermann Ney,et al. Comparison of optimization methods for discriminative training criteria , 1997, EUROSPEECH.
[3] Nicolas Monmarché,et al. Algorithmes de fourmis artificielles : applications à la classification et à l'optimisation. (Artificial ant based algorithms applied to clustering and optimization problems) , 2000 .
[4] N. Goodwin,et al. Learning to Detect Objects in Images via a Sparse, Part-Based Representation , 2004 .
[5] Jeng-Shyang Pan,et al. Optimization of HMM by the Tabu Search Algorithm , 2004, J. Inf. Sci. Eng..
[6] Thomas Kiel Rasmussen,et al. Improved Hidden Markov Model training for multiple sequence alignment by a particle swarm optimization-evolutionary algorithm hybrid. , 2003, Bio Systems.
[7] Sean R. Eddy,et al. Profile hidden Markov models , 1998, Bioinform..
[8] Nicolas Monmarché,et al. An Exponential Representation in the API Algorithm for Hidden Markov Models Training , 2005, Artificial Evolution.
[9] J. Movellan. Tutorial on Hidden Markov Models , 2006 .
[10] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[11] Keith Vertanen,et al. An Overview of Discriminative Training for Speech Recognition , 2005 .
[12] Andrew J. Viterbi,et al. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm , 1967, IEEE Trans. Inf. Theory.
[13] Yoshua Bengio,et al. Markovian Models for Sequential Data , 2004 .
[14] Karl-Heinz Hoffmann,et al. Optimizing Simulated Annealing , 1990, PPSN.
[15] D. B. Paul. Training of HMM recognizers by simulated annealing , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.
[16] Sebastien Aupetit. Contributions aux Modèles de Markov Cachés : métaheuristiques d'apprentissage, nouveaux modèles et visualisation de dissimilarité. (Contributions to Hidden Markov Models: metaheuristics for training, new models and dissimilarity visualization) , 2005 .
[17] Alain Hertz,et al. A TUTORIAL ON TABU SEARCH , 1992 .
[18] Goldberg,et al. Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.
[19] Fred W. Glover,et al. Future paths for integer programming and links to artificial intelligence , 1986, Comput. Oper. Res..
[20] Sven Anderson,et al. Training hidden Markov Models using population-based learning , 1999 .
[21] L. Baum,et al. An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process , 1972 .
[22] Rich Caruana,et al. Removing the Genetics from the Standard Genetic Algorithm , 1995, ICML.
[23] René Thomsen. Evolving the Topology of Hidden Markov Models Using Evolutionary Algorithms , 2002, PPSN.
[24] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[25] Ufr Médecine,et al. L'UNIVERSITE FRANCOIS RABELAIS de TOURS , 2007 .
[26] Fred W. Glover,et al. Tabu Search - Part I , 1989, INFORMS J. Comput..
[27] Lawrence K. Saul,et al. Maximum likelihood and minimum classification error factor analysis for automatic speech recognition , 2000, IEEE Trans. Speech Audio Process..
[28] H. Bourlard,et al. Links Between Markov Models and Multilayer Perceptrons , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[29] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[30] David J. Hand,et al. Intelligent Data Analysis: An Introduction , 2005 .
[31] Olivier Cappé,et al. Ten years of HMMs , 2001 .
[32] Jr. G. Forney,et al. Viterbi Algorithm , 1973, Encyclopedia of Machine Learning.
[33] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[34] Yariv Ephraim,et al. Estimation of hidden Markov model parameters by minimizing empirical error rate , 1990, International Conference on Acoustics, Speech, and Signal Processing.
[35] Slimane,et al. 5 - Apprentissage non-supervisé d'images par hybridation génétique d'une chaîne de Markov cachée , 1999 .
[36] Fred Glover,et al. Tabu Search - Part II , 1989, INFORMS J. Comput..
[37] Wojciech Pieczynski. Arbres de Markov Triplet et fusion de Dempster-Shafer , 2003 .
[38] EngineeringSwarthmore CollegeSwarthmore,et al. Training Hidden Markov Models using Population-Based Learning , 1999 .
[40] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[41] L. Baum,et al. An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology , 1967 .
[42] J. Dréo,et al. Métaheuristiques pour l'optimisation difficile , 2003 .
[43] Nicolas Monmarché,et al. On how Pachycondyla apicalis ants suggest a new search algorithm , 2000, Future Gener. Comput. Syst..
[44] Jr. G. Forney,et al. The viterbi algorithm , 1973 .
[45] Biing-Hwang Juang,et al. The segmental K-means algorithm for estimating parameters of hidden Markov models , 1990, IEEE Trans. Acoust. Speech Signal Process..
[46] Sadik Kapadia,et al. Discriminative Training of Hidden Markov Models , 1998 .
[47] A. Berchtold. The double chain markov model , 1999 .
[48] Dan Roth,et al. Learning to detect objects in images via a sparse, part-based representation , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[49] Yoram Singer,et al. The Hierarchical Hidden Markov Model: Analysis and Applications , 1998, Machine Learning.
[50] Andy Harter,et al. Parameterisation of a stochastic model for human face identification , 1994, Proceedings of 1994 IEEE Workshop on Applications of Computer Vision.