Jose Gamez - Academia.edu (original) (raw)

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Papers by Jose Gamez

Research paper thumbnail of Complex patterns of male germline instability and somatic mosaicism in myotonic dystrophy type 1

European Journal of Human Genetics, 2000

Research paper thumbnail of Progression of somatic CTG repeat length heterogeneity in the blood cells of myotonic dystrophy patients

Human Molecular Genetics, 1998

Research paper thumbnail of PS-18-5 Distal myopathy of Miyoshi. A clinical, pathologic and quantitative EMG study of 4 cases

Electroencephalography and Clinical Neurophysiology/Electromyography and Motor Control, 1995

Research paper thumbnail of Incremental compilation of Bayesian networks

Uncertainty in Artificial Intelligence, 2003

Research paper thumbnail of Incremental compilation of Bayesian networks

Uncertainty in Artificial Intelligence, 2003

Research paper thumbnail of Searching for the best elimination sequence in Bayesian networks by using ant colony optimization

Pattern Recognition Letters, 2002

The knowledge base of a probabilistic expert system is usually represented as a Bayesian network.... more The knowledge base of a probabilistic expert system is usually represented as a Bayesian network. Most of the knowledge engineering tools used in the development of probabilistic expert systems do not carry out the inference process directly over the network, but in a secondary graphical structure called a junction tree. The efficiency of inference (propagation) algorithms depends on the size

Research paper thumbnail of Searching for the best elimination sequence in Bayesian networks by using ant colony optimization

Pattern Recognition Letters, 2002

The knowledge base of a probabilistic expert system is usually represented as a Bayesian network.... more The knowledge base of a probabilistic expert system is usually represented as a Bayesian network. Most of the knowledge engineering tools used in the development of probabilistic expert systems do not carry out the inference process directly over the network, but in a secondary graphical structure called a junction tree. The efficiency of inference (propagation) algorithms depends on the size

Research paper thumbnail of Partial abductive inference in Bayesian belief networks using a genetic algorithm

Pattern Recognition Letters, 1999

Research paper thumbnail of Partial abductive inference in Bayesian belief networks using a genetic algorithm

Pattern Recognition Letters, 1999

Research paper thumbnail of Partial abductive inference in Bayesian belief networks - an evolutionary computation approach by using problem-specific genetic operators

IEEE Transactions on Evolutionary Computation, 2002

Research paper thumbnail of Partial abductive inference in Bayesian belief networks - an evolutionary computation approach by using problem-specific genetic operators

IEEE Transactions on Evolutionary Computation, 2002

Research paper thumbnail of Low-Complexity Heterogeneous Video Transcoding Using Data Mining

IEEE Transactions on Multimedia, 2008

Research paper thumbnail of Low-Complexity Heterogeneous Video Transcoding Using Data Mining

IEEE Transactions on Multimedia, 2008

Research paper thumbnail of Ant colony optimization for learning Bayesian networks

International Journal of Approximate Reasoning, 2002

Research paper thumbnail of Ant colony optimization for learning Bayesian networks

International Journal of Approximate Reasoning, 2002

Research paper thumbnail of Complex patterns of male germline instability and somatic mosaicism in myotonic dystrophy type 1

European Journal of Human Genetics, 2000

Research paper thumbnail of Progression of somatic CTG repeat length heterogeneity in the blood cells of myotonic dystrophy patients

Human Molecular Genetics, 1998

Research paper thumbnail of PS-18-5 Distal myopathy of Miyoshi. A clinical, pathologic and quantitative EMG study of 4 cases

Electroencephalography and Clinical Neurophysiology/Electromyography and Motor Control, 1995

Research paper thumbnail of Incremental compilation of Bayesian networks

Uncertainty in Artificial Intelligence, 2003

Research paper thumbnail of Incremental compilation of Bayesian networks

Uncertainty in Artificial Intelligence, 2003

Research paper thumbnail of Searching for the best elimination sequence in Bayesian networks by using ant colony optimization

Pattern Recognition Letters, 2002

The knowledge base of a probabilistic expert system is usually represented as a Bayesian network.... more The knowledge base of a probabilistic expert system is usually represented as a Bayesian network. Most of the knowledge engineering tools used in the development of probabilistic expert systems do not carry out the inference process directly over the network, but in a secondary graphical structure called a junction tree. The efficiency of inference (propagation) algorithms depends on the size

Research paper thumbnail of Searching for the best elimination sequence in Bayesian networks by using ant colony optimization

Pattern Recognition Letters, 2002

The knowledge base of a probabilistic expert system is usually represented as a Bayesian network.... more The knowledge base of a probabilistic expert system is usually represented as a Bayesian network. Most of the knowledge engineering tools used in the development of probabilistic expert systems do not carry out the inference process directly over the network, but in a secondary graphical structure called a junction tree. The efficiency of inference (propagation) algorithms depends on the size

Research paper thumbnail of Partial abductive inference in Bayesian belief networks using a genetic algorithm

Pattern Recognition Letters, 1999

Research paper thumbnail of Partial abductive inference in Bayesian belief networks using a genetic algorithm

Pattern Recognition Letters, 1999

Research paper thumbnail of Partial abductive inference in Bayesian belief networks - an evolutionary computation approach by using problem-specific genetic operators

IEEE Transactions on Evolutionary Computation, 2002

Research paper thumbnail of Partial abductive inference in Bayesian belief networks - an evolutionary computation approach by using problem-specific genetic operators

IEEE Transactions on Evolutionary Computation, 2002

Research paper thumbnail of Low-Complexity Heterogeneous Video Transcoding Using Data Mining

IEEE Transactions on Multimedia, 2008

Research paper thumbnail of Low-Complexity Heterogeneous Video Transcoding Using Data Mining

IEEE Transactions on Multimedia, 2008

Research paper thumbnail of Ant colony optimization for learning Bayesian networks

International Journal of Approximate Reasoning, 2002

Research paper thumbnail of Ant colony optimization for learning Bayesian networks

International Journal of Approximate Reasoning, 2002

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