V. Balasubramanian, Equivalence and reduction of hidden Markov models, Master's thesis, Department of Electrical Engineering and Computer Science, MIT, issued as AI Technical Report 1370, 1993. Home/Search Document Details and Download
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Gibbs-Markov Models - Lafferty (1995) (3 citations) (Correct)
.... case of the EM algorithm) and for finding the most probable state sequence for a given output string (the Viterbi algorithm) As an indication of the simplicity of HMM s, it is known that the problem of determining when two HMM s are probabilistically equivalent can be decided in polynomial time [4]. A thorough discussion of the mechanics of training and decoding HMM s, as well as a discussion of HMM neural network hybrids related to Gibbs Markov models is given in [18] HMM s and stochastic grammars are fundamentally limited, however, in their modeling capabilities. The Markov assumption, ....
V. Balasubramanian, Equivalence and reduction of hidden Markov models, Master's thesis, Department of Electrical Engineering and Computer Science, MIT, issued as AI Technical Report 1370, 1993.
Gibbs-Markov Models - John Lafferty School (1996) (1 citation) (Correct)
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V. Balasubramanian, Equivalence and reduction of hidden Markov models, Master's thesis, Department of Electrical Engineering and Computer Science, MIT, issued as AI Technical Report 1370, 1993.
Probabilistic Finite-State Machines - Part II - Vidal, al. (Correct)
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V. Balasubramanian, "Equivalence and reduction of Hidden Markov Models," Massachusetts Institute of Technology, Tech. Rep. AITR-1370, 1993.
Appendix A Notation - Processes Alphabet (Correct)
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V. Balasubramanian, "Equivalence and reduction of hidden markov models," Tech. Rep. A.I. Techhnical Report No. 1370, Massachusetts Institute of Technology, January 1993.
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