Learning deep architectures for AI

Bengio, Yoshua

Learning deep architectures for AI by Yoshua Bengio. - Hanover, Mass. : Now Publishers, 2009 - 131 P. : il. - Foundations and trends in machine learning, .

Incluye bibliografia (p. : 113.127)

1. Introduction -- 2. Theoretical advantages of deep architectures -- 3. Local vs non-local generalization -- 4. Neural networks for deep architectures -- 5. Energy-based models and Boltzmann machines -- 6. Greedy layer-wise training of deep architectures -- 7. Variants of RBMs and auto-encoders -- 8. Stochastic variational bounds for joint optimization of DBN layers -- 9. Looking forward -- 10. Conclusion

9781601982940


INTELIGENCIA ARTIFICIAL
ALGORITMOS COMPUTACIONALES
TEORIA DEL APRENDIZAJE COMPUTACIONAL

006.31 / B466