Diferencia entre revisiones de «MaterialesMgranaActiveLearning»
De Grupo de Inteligencia Computacional (GIC)
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* entrenamiento de redes neuronales, LVQ [http://www.sciencedirect.com/science/article/pii/S0167404807001101], probabilistic RBF [http://www.sciencedirect.com/science/article/pii/S0925231208002117], canonical component analysis CCA [http://www.sciencedirect.com/science/article/pii/S0925231210003334], | * entrenamiento de redes neuronales, LVQ [http://www.sciencedirect.com/science/article/pii/S0167404807001101], probabilistic RBF [http://www.sciencedirect.com/science/article/pii/S0925231208002117], canonical component analysis CCA [http://www.sciencedirect.com/science/article/pii/S0925231210003334], | ||
* aproximacion de ''value function'' en ''reinforcement learning'' [http://www.sciencedirect.com/science/article/pii/S0893608010000031] | * aproximacion de ''value function'' en ''reinforcement learning'' [http://www.sciencedirect.com/science/article/pii/S0893608010000031] | ||
* theoretical computer science [http://www.sciencedirect.com/science/article/pii/S0304397510007620], con regularizacion adaptativa [http://www.sciencedirect.com/science/article/pii/S0031320311000938], ensemble with model selection [http://www.sciencedirect.com/science/article/pii/S0893608008001329], optimal sampling [http://www.sciencedirect.com/science/article/pii/S0925231207000355], agnostic active learning [http://www.sciencedirect.com/science/article/pii/S0022000008000652] | * theoretical computer science [http://www.sciencedirect.com/science/article/pii/S0304397510007620], con regularizacion adaptativa [http://www.sciencedirect.com/science/article/pii/S0031320311000938], ensemble with model selection [http://www.sciencedirect.com/science/article/pii/S0893608008001329], optimal sampling [http://www.sciencedirect.com/science/article/pii/S0925231207000355], agnostic active learning [http://www.sciencedirect.com/science/article/pii/S0022000008000652], AUC maximization [http://www.sciencedirect.com/science/article/pii/S0925231210000093] | ||
Revisión del 01:33 5 jul 2011
Active learning [1] es una linea de trabajo de interés actual con aplicaciones a proceso de imagen de percepcion remota o imagen medica. Implica el control sobre los datos usados en el entrenamiento, en el límite implica la interacción con el usuario y es una forma de 'reinforcement learning y de relevance feedback
- adaptación de clasificadores de imagenes remotas [2]
- image retrieval [3], [4],[5],
- webpage clasification y otras [6]
- microarray data [7]
- speech recognition [8]
- network intrusion detection [9]
- entrenamiento de redes neuronales, LVQ [10], probabilistic RBF [11], canonical component analysis CCA [12],
- aproximacion de value function en reinforcement learning [13]
- theoretical computer science [14], con regularizacion adaptativa [15], ensemble with model selection [16], optimal sampling [17], agnostic active learning [18], AUC maximization [19]
